machine learning scientist

The New York Times

<div><div><div><div><div><div>The mission of The New York Times is to seek the truth and help people understand the world. That means independent journalism is at the heart of all we do as a company. It's why we have a world-renowned newsroom that sends journalists to report on the ground from nearly 160 countries. It's why we focus deeply on how our readers will experience our journalism, from print to audio to a world-class digital and app destination. And it's why our business strategy centers on making journalism so good that it's worth paying for.
</div>
</div></div></div></div>About the Role, Mission or Department Overview

The New York Times is hiring a Machine Learning Scientist to join the New A.I. Products &amp; Platforms mission. We are a team building the next generation of reader-facing A.I. experiences for one of the world's most trusted news organizations. 


You will join a team of ML scientists developing embedding models and retrieval algorithms to power new A.I. experiences across our products. You will design and train embedding models for representation learning and fine-tune language models for custom use cases and content enrichment. Your work will allow teams across the company to build, deploy, and manage applications that use large language models (LLMs) to promote our journalism and our business. You will report to our Director, Machine Learning. This is a hybrid remote/in-office role. 


Responsibilities:
<ul>
<li>You will design and train embedding models for representation learning, for example using transformer encoders and Two Tower architectures.
</li>
<li>You will fine-tune and evaluate language models for custom use cases and content enrichment.
</li>
<li>You will contribute to shared practices around evaluation, responsible A.I. use, and what &quot;good&quot; is inside an organization where judgment and independence are important
</li>
<li>You will implement and deploy machine learning and AI research with robustness and reproducibility, with consideration of risks and trade-offs
</li>
<li>You will adapt or develop ML and AI algorithms in cases when existing techniques are insufficient, while implementing simple approaches
</li>
<li>You will communicate complex ideas in machine learning and AI while collaborating with all kinds of colleagues in engineering, analytics, product management, marketing, editorial, and executive leadership groups
</li>
<li>Demonstrate support and understanding of our value of journalistic independence and a strong commitment to our mission to seek the truth and help people understand the world.</li></ul> 

Basic Qualifications:
<ul>
<li>PhD, MS + 2 years experience, or 3+ years work experience in machine learning, statistics, computational social science, applied mathematics, or another quantitative/computational discipline
</li>
<li>2+ years experience with open source machine learning or statistical analysis tools
</li>
<li>2+ years coding experience in Python
</li>
<li>2+ years experience in SQL and manipulating large structured or unstructured datasets for analysis
</li>
<li>1+ years of experience with deep learning architectures, fine-tuning, embeddings and Pytorch or Tensorflow</li></ul> 

Preferred Qualifications:
<ul>
<li>1+ years of experience with information retrieval or search systems
</li>
<li>1+ years of experience translating ambiguous business questions into machine learning problems
</li>
<li>1+ years of experience building data products, either internal or consumer-facing
</li>
</ul>REQ-020337<div> 
For roles in the U.S., dependent on your role, you may be eligible for variable pay, such as an annual bonus and restricted stock. Benefits may include medical, dental and vision benefits, Flexible Spending Accounts (F.S.A.s), a company-matching 401(k) plan, paid vacation, paid sick days, paid parental leave, tuition reimbursement and professional development programs.

For roles outside of the U.S., information on benefits will be provided during the interview process.

We're excited to learn more about you and your experience. To keep our hiring process as fair and authentic as possible, we ask that you submit your own work and not use GenAI tools to generate substantive content during the application and interview process.

If you're an Engineering candidate, we'll let you know what specific GenAI tools you are permitted to use for your technical assessment.

The New York Times Company is committed to being the world's best source of independent, reliable and quality journalism. To do so, we embrace a diverse workforce that has a broad range of backgrounds and experiences across our ranks, at all levels of the organization. We encourage people from all backgrounds to apply.

We are an Equal Opportunity Employer and do not discriminate on the basis of an individual's sex, age, race, color, creed, national origin, alienage, religion, marital status, pregnancy, sexual orientation or affectional preference, gender identity and expression, disability, genetic trait or predisposition, carrier status, citizenship, veteran or military status and other personal characteristics protected by law. All applications will receive consideration for employment without regard to legally protected characteristics. The U.S. Equal Employment Opportunity Commission (EEOC)'s Know Your Rights Poster is available here.

The New York Times Company will provide reasonable accommodations as required by applicable federal, state, and/or local laws. Individuals seeking an accommodation for the application or interview process should email reasonable.accommodations@nytimes.com. Emails sent for unrelated issues, such as following up on an application, will not receive a response.

The Company encourages those with criminal histories to apply, and will consider their applications in a manner consistent with applicable &quot;Fair Chance&quot; laws, including but not limited to the NYC Fair Chance Act, the Los Angeles Fair Chance Initiative for Hiring Ordinance, the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act.

For information about The New York Times' privacy practices for job applicants click here.

Please beware of fraudulent job postings. Scammers may post fraudulent job opportunities, and they may even make fraudulent employment offers. This is done by bad actors to collect personal information and money from victims. All legitimate job opportunities from The New York Times will be accessible through The New York Times careers site. The New York Times will not ask job applicants for financial information or for payment, and will not refer you to a third party to do so. You should never send money to anyone who suggests they can provide employment with The New York Times.

If you see a fake or fraudulent job posting, or if you suspect you have received a fraudulent offer, you can report it to The New York Times at NYTapplicants@nytimes.com. You can also file a report with the Federal Trade Commission or your state attorney general.</div></div>

Machine Learning Scientist, New AI Products and Platforms

Amazon.com

<div><h2 class="jobSectionHeader">DESCRIPTION</h2><div>
The Amazon Fulfillment Technologies (AFT) Science team is looking for an exceptional Data Scientist, with strong analytical skills and understanding of optimization, to partner with scientists, engineers, product managers, and operations leaders, and develop data-driven solutions for one of the most complex systems in the world: Amazon&rsquo;s Fulfillment Network. At AFT Science, we design, build and deploy optimization, simulation, and machine learning solutions to power the production systems running at world wide Amazon Fulfillment Centers. We solve a wide range of problems that are encountered in the network, including labor planning and staffing, demand prioritization, stow guidance, pick scheduling, and flow process optimization. We are tasked to develop innovative, scalable, and reliable science-driven solutions that are beyond the published state of art in order to run frequently (ranging from every few minutes to every few hours per use case) and continuously in our large scale network. 
 
Key job responsibilities 
As an Data Scientist, you will work with other scientists, software engineers, product managers, and operations leaders to develop scientific solutions and analytics using a variety of tools and observe direct impact to process efficiency and associate experience in the fulfillment network. Key responsibilities include: 
<ul><li>Design and conduct rigorous experimental design for production pilots to evaluate the impact of the solution and improve model performance
</li><li>Lead the end-to-end lifecycle of forecasting models, from research and experimentation through production launch including defining success metrics, obtaining stakeholder sign-off, and managing rollout</li><li>Develop and deploy production grade ML and statistical models using Python, Scala, SQL, and related tools</li><li>Perform large-scale exploratory data analysis to uncover patterns, identify opportunities, and inform model development</li><li>Translate complex science findings into clear insights and recommendations for technical and non-technical stakeholders at all levels</li><li>Contribute to Amazon's scientific community and the broader research field through collaboration and presentation in top-tier venues</li></ul> 
About the team 
Amazon Fulfillment Technology (AFT) designs, develops and operates the end-to-end fulfillment technology solutions for all Amazon Fulfillment Centers (FC). We harmonize the physical and virtual world so Amazon customers can get what they want, when they want it. 
 
The AFT Science team has expertise in operations research, optimization, statistics, simulation, and machine learning. We also have domain expertise in the operational processes within the FCs and their defects. We prioritize advancements that support AFT tech teams and focus areas rather than specific fields of research or individual business partners. We influence each stage of innovation from inception to deployment which includes both developing novel solutions or improving existing approaches. Resulting production systems rely on a diverse set of technologies, our teams therefore invest in multiple specialties as the needs of each focus area evolves.</div><h2 class="jobSectionHeader">
BASIC QUALIFICATIONS</h2><ul><li>Bachelor's degree or above in a quantitative field, or Master's degree</li><li>3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience</li><li>3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience</li><li>Experience with forecasting and statistical analysis</li><li>Experience processing, filtering, and presenting large quantities (hundreds of millions/billions of rows) of data</li><li>Familiarity with using the Gen AI technology suite for productivity enhancement</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>Experience in Python, Perl, or another scripting language</li><li>Experience effectively communicating complex concepts through written and verbal communication</li><li>2+ years of ML or optimization and algorithms implementation experience</li><li>Ability to write and maintain production level code is a plus</li><li>Ability to maintain end to end data pipelines and metrics at scale</li><li>Experience working on multi-team, cross-disciplinary projects</li></ul> 
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. 
 
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner. 
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life &amp; AD&amp;D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits. 
USA, WA, Bellevue - 136,000.00 - 184,000.00 USD annually</div>

Data Scientist II, Amazon Fulfillment Technology (AFT) Science

Survice Engineering Company

<div>Join Us in Making a Difference in the Lives of Those Defending Our Nation!
Why SURVICE?
Come join the SURVICE Engineering mission to protect, enhance, and enable those who defend the United States. Since 1981, we have supported the DoD community, as well as Homeland Security, advanced technologies, environmental, and commercial markets. Our employees have backgrounds in engineering, physics, mathematics, chemistry, computer science, acquisition, technical writing, training, and other technical and administrative fields. And many of our personnel have DoD and/or operational military experience. If you're looking for a challenging and rewarding career with a leading organization, come see what we can offer you!
Position
Computational Data Scientist<ul><li>
Location: Aberdeen Proving Ground, Maryland</li><li>
Security Clearance: Active Clearance or Eligible to Obtain - U.S. citizenship required</li><li>
Salary: $115,000 - $130,000 Depending on Experience and Education</li><li>
Travel: 5%</li><li>
Benefits: SURVICE Engineering offers a total rewards package to include competitive salaries, comprehensive insurance options, paid time off, 401k, flexible spending, tuition reimbursement.</li></ul>
Position Summary
SURVICE Engineering is currently seeking a Computational Data Scientist to support our Aberdeen Research Operation. You will accelerate your career and become an integral team member within the defense community.
Primary Duties and Responsibilities<ul><li>
Carry out forward-looking programs of materials research and process modeling leveraging data science methodologies and tools including artificial intelligence, machine learning (ML), probabilistic graph models, neural networks, or other emergent techniques.</li><li>
Work with a multidisciplinary team of ARL experimental, theoretical, and computational scientists through decision making aids such as visual analytics and human-in-the-loop strategies to improve scientific efficiency and impact.</li><li>
Apply learning algorithms on high-dimensional, complex and/or streaming data sets with limited labels and of diverse quality for smart decision making.</li><li>
Pursue data processing of heterogeneous types from numeric, digital objects, images, structured to unstructured from data capture, data integration, data cleaning to data management.</li><li>
Interface with data scientists in academic, industrial and government labs to identify and transition cutting edge tools for use at ARL, and work with outside partners to fill critical gaps in skills and capabilities.</li><li>
Prepare presentations and written documents summarizing efforts in Government format</li></ul>
Minimum Qualifications of Computational Data Scientist 
Masters of Science or PhD in Computer Science or Math related discipline and 3+ years of relevant experience. Exceptional candidates with less experience will be considered. Candidates are not required to possess all qualifications; if you possess some of the desired qualifications, please apply.<ul><li>
MS or PhD concentration in machine learning with at least three (3) independent projects including internships and thesis work OR minimum of five (5) years of dedicated experience with machine learning.</li><li>
Practical experience in applying data science to model complex real-world problems.</li><li>
Proficient in using Python and AI/ML models.</li><li>
Experience in communicating results through reports and presentations.</li></ul>
About Us
SURVICE Engineering is a nationally recognized, single-source engineering service provider for Government and Industry organizations involved in all phases of the systems engineering process. Our employees are our most valuable asset, and they are proud to have supported the development, testing, analysis, and modeling and simulation (M&amp;S) of many of the major U.S. air, land, and sea combat systems in the field today. They have also contributed their expertise to other vital national defense programs and technologies that involve survivability, cybersecurity, information technology/management, software engineering, unmanned aerial systems (UASs), and metrology/reverse engineering. 
SURVICE Engineering is an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, or any other characteristic protected by law. VEVRAA Federal Contractor.</div>

Computational Data Scientist

<div><h2 class="jobSectionHeader">DESCRIPTION</h2>
The WW DSP Analytics team is a centralized analytics organization within Amazon's Last Mile Delivery Service Partner (DSP) program. We build best-in-class solutions that enable data-driven decision making across our global DSP ecosystem. Our team partners with internal stakeholders, DSP owners, and cross-functional teams to deliver insights that drive operational excellence, business growth, and the success of small business owners in Last Mile delivery. Our work directly impacts customer experience, driver and station associate experience, DSP success, and Amazon's sustainable growth. 
 
The goal of Amazon&rsquo;s DSP organization is to exceed the expectations of our customers by ensuring that their orders, no matter how large or small, are delivered as quickly, accurately, and cost effectively as possible. To meet this goal, Amazon is continually striving to innovate and provide best in class delivery experience through the introduction of pioneering new products and services in the last mile delivery space. Come join us and help us make history! 
 
We are seeking a passionate Data Scientist with deep expertise in optimization and causal inference to join our team. You will work on some of the most challenging problems in DSP delivery planning and the business health space, applying data science rigor to improve how decisions are made and drive outcomes at scale. 
 
Key job responsibilities 
Develop Science Solutions for DSP Capacity Planning &amp; Business Health: Design and implement data science solutions that optimize Delivery Service Partner (DSP) capacity allocation and business health measurement across the global DSP network. Leverage deep expertise in mathematical optimization and causal inference to identify opportunities for improving capacity planning models, volume share calibration methodologies, and business health measurement systems that drive partner sustainability. 
Analyze Sentiment Risks &amp; Business Health Metrics: Analyze sentiment risks and enhance algorithms that support DSP program management, including business health indicators, capacity reliability models, and partner viability frameworks that inform intervention strategies. 
Translate Business Requirements into Mathematical Models: Demonstrate strategic thinking by translating high-level DSP capacity planning and business health improvement requirements into optimization formulations and predictive models, and applying them to quantify return on investment for policy changes and network interventions. 
Build Production-Scale Analytics: Contribute to the development and deployment of scalable data models, dashboards, and automated reporting systems that enable self-service analytics for DSP stakeholders and surface business health signals at scale. 
Accelerate GenAI Footprint: Partner with Data Engineers to expand our GenAI tools and improve developer productivity, while raising the bar on data quality and enabling intelligent automation across capacity planning workflows. 
Conduct Independent Data Analysis: Mine and analyze complex datasets across multiple domains, business health metrics, financial data, capacity signals, and operational data, using programming and statistical tools to generate actionable insights. 
Thrive in a Collaborative Environment: Excel in a fast-paced analytics organization that encourages collaborative and creative problem-solving. Measure and communicate analytical risks, constructively critique peer work, and align research focuses with DSP capacity planning strategic needs. 
Partner Cross-Functionally: Work closely with Business Intelligence Engineers, capacity planning teams, and DSP stakeholders to define KPIs, validate analytical approaches, and ensure insights drive meaningful outcomes. 
 
About the team 
We are the WW DSP Analytics team with the vision to enable data, insights and science driven decision-making. We have exceptionally talented and fun loving team members. In our team, you will have the opportunity to dive deep into complex business and data problems, drive large scale technical solutions and raise the bar for operational excellence. We love to share ideas and learning with each other. We believe in promoting and using ideas to disrupt the status quo.<h2 class="jobSectionHeader">
BASIC QUALIFICATIONS</h2><ul><li>Master's degree in econometrics, statistics, industrial engineering, operations research, optimization, data mining, analytics, or equivalent quantitative field, or experience working in Science, Technology, Engineering, or Mathematics (STEM)</li><li>3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience</li><li>3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience</li><li>2+ years of data scientist experience</li><li>2+ years of a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science experience</li><li>1+ years of working with or evaluating AI systems experience</li><li>Experience applying quantitative analysis to solve business problems and making data-driven business decisions</li><li>Experience effectively communicating complex concepts through written and verbal communication</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>Ph.D. in econometrics, statistics, industrial engineering, operations research, optimization, data mining, analytics, or equivalent quantitative field</li><li>Experience in a ML or data scientist role with a large technology company</li><li>Knowledge of machine learning concepts and their application to reasoning and problem-solving</li><li>Experience implementing algorithms using both toolkits and self-developed code</li><li>Experience in defining and creating benchmarks for assessing GenAI model performance</li><li>Experience working on multi-team, cross-disciplinary projects</li></ul> 
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. 
 
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner. 
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life &amp; AD&amp;D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits. 
USA, WA, Bellevue - 136,000.00 - 184,000.00 USD annually</div>

Data Scientist II, WW DSP Analytics

New York University Abu Dhabi

<div>
 The Center for Technology, Economics, and Development (CTED) at New York University Abu Dhabi (NYUAD) invites applications from individuals to be appointed as a Junior Research Scientist (AI-Blockchain Project) for a one-year period, with the possibility of renewal conditional on excellent performance.
 
 
 The Junior Research Scientist (AI-Blockchain Research) will support advanced, quantitatively intensive research at CTED with a primary focus on artificial intelligence, machine learning, mathematical modeling, and computational analysis. The Junior Research Scientist will play a central role in supporting research design, algorithmic development, data analysis, and coding tasks across CTED&rsquo;s interdisciplinary projects. Working under the direction of the Principal Investigator (PI), Dr. Yaw Nyarko, and Co-Principal Investigator (Co-PI), Dr. Ra&scaron;a Karapand&zcaron;a, the Junior Research Scientist will contribute to AI-driven and blockchain-enabled research related to commodities markets and economic development. The role requires strong foundations in mathematics and computer science, including statistical learning, optimization, simulation, and algorithmic reasoning. The successful candidate will use programming and computational tools (including Python, MATLAB, and related libraries) to develop, test, and evaluate machine learning models; review, proofread, and execute formal mathematical proofs; implement optimization and simulation-based methods; and analyze large and complex datasets. Responsibilities include supporting experimental and field-based research, preparing literature reviews, translating complex AI and mathematical findings into clear written outputs, and contributing to research reports, concept notes, and academic publications.
 
 
 Candidates must hold a Master&rsquo;s degree in Computer Science, Data Science, Mathematics or a related field (e.g., Economics with a strong mathematics background). and have less than five years of relevant research experience; or hold a Bachelor&rsquo;s degree in a relevant field with any level of research experience. Applicants must have extensive coding experience, and preferably, applicants will have experience conducting field research in emerging countries and working on randomized controlled trials (RCTs). Applicants with experience working in programming languages such as Python, JavaScript, and/or MATLAB, a strong interest in economic and quantitative research and the willingness to learn about the blockchain, are encouraged to apply. Experience in web development, blockchain, commodities markets, and technology and economic development will be considered a plus. The successful candidate will work in a multidisciplinary environment, working autonomously, but as a team member under the direction of the Principal Investigator.
 
 
 The terms of employment are very competitive. Applications will be accepted immediately, and candidates will be considered until the position is filled. For consideration, applicants need to submit a cover letter, curriculum vitae/resume, transcript of degree, and one academic writing sample, and 2 contact references, all in PDF format. If you have any questions, please email amp330@nyu.edu.
 
 
 NYUAD is an equal-opportunity employer. We welcome applications from all qualified candidates and seek individuals who will contribute to the excellence and vibrancy of our academic community.
 
 
 Applications are welcome from all qualified candidates. In line with UAE regulations, Emirati candidates are encouraged to apply.
 
 
 
 About NYU Abu Dhabi
 
 
 
 https://nyuad.nyu.edu/en/
 
 
 NYU Abu Dhabi is the first comprehensive liberal arts and research campus in the Middle East to be operated abroad by a major American research university. Times Higher Education ranks NYU among the top 30 universities in the world, making NYU Abu Dhabi the highest-ranked university in the UAE and MENA region. NYU Abu Dhabi has integrated a highly selective undergraduate curriculum across the disciplines with a world center for advanced research and scholarship. The university enables its students in the sciences, engineering, social sciences, humanities, and arts to succeed in an increasingly interdependent world and advance cooperation and progress on humanity&rsquo;s shared challenges. NYU Abu Dhabi&rsquo;s high-achieving students have come from over 120 countries and speak over 100 languages. Together, NYU's campuses in New York, Abu Dhabi, and Shanghai form the backbone of a unique global university, giving faculty and students opportunities to experience varied learning environments and immersion in other cultures at one or more of the numerous study-abroad sites NYU maintains on six continents.
 
 
 NYUAD is committed to upholding a culture of non-discrimination, anti-harassment, dignity, and mutual respect; providing equal access and opportunity; and fostering academic excellence in learning, research, and teaching.
 
 
 Students are drawn from among the world&rsquo;s best. They are bright, intellectually passionate, and committed to building a campus environment anchored in mutual respect, understanding, and care. The NYUAD undergraduate student body has garnered an impressive record of scholarships, graduate-school admissions, and other global honors. Graduate education is an area of growth for the University; the current graduate student population of over 100 students is expected to expand in the next decade as doctoral programs are developed.
 
 
 Working for NYUAD
 
 
 At NYUAD, we recognize that Abu Dhabi is more than where you work; it&rsquo;s your home. In order for faculty/academic staff to thrive, we offer a comprehensive benefits package. This starts with a generous relocation allowance; educational assistance for your dependents; access to health and wellness services; and more. NYUAD is committed to faculty/academic staff success throughout the academic trajectory, providing support for ambitious and world-class research projects and innovative, interactive teaching approaches. Support for dual-career families is a priority. Visit our website for more information on benefits for you and your dependents.
 
 
 Join NYU Abu Dhabi, an exceptional place for exceptional people.
 
 
 NYUAD values belonging and respect; such principles are fundamental to the university&rsquo;s commitment to excellence. NYUAD is an equal-opportunity employer. We welcome applications from all qualified candidates and seek individuals who will contribute to our vibrant, multidisciplinary research and teaching community. Multidisciplinary research and exceptional teaching in a global campus community are hallmarks of the University&rsquo;s mission.
 
 
 
 Equal Employment Opportunity Statement
 
 
 
 
 For people in the EU, click here for information on your privacy rights under GDPR: www.nyu.edu/it/gdpr
 
 
 
 NYU is an Equal Opportunity Employer and is committed to a policy of equal treatment and opportunity in every aspect of its recruitment and hiring process without regard to age, alienage, caregiver status, childbirth, citizenship status, color, creed, disability, domestic violence victim status, ethnicity, familial status, gender and/or gender identity or expression, marital status, military status, national origin, parental status, partnership status, predisposing genetic characteristics, pregnancy, race, religion, reproductive health decision making, sex, sexual orientation, unemployment status, veteran status, or any other legally protected basis. All interested persons are encouraged to apply for vacant positions at all levels.
 
 
 
 Sustainability Statement
 
 
 
 NYU aims to be among the greenest urban campuses in the country and carbon neutral by 2040. Learn more at nyu.edu/sustainability
</div>

Junior Research Scientist in the Division of Social Science (CTED) - Dr. Yaw Nyarko

Cambia Health Solutions

<div><div>AI Scientist Senior II
Hybrid role (3 days/week in office) at our Burlington, Renton, Spokane, Vancouver, Portland, Medford, Salt Lake City, Boise, Lewiston, or Fargo offices.
Candidates must reside within commutable distance of that location or be willing to relocate.
Build a career with purpose. Join our Cause to create a person-focused and economically sustainable health care system.
Who We Are Looking For:
Every day, Cambia's Applied AI Team is living our mission to make health care easier and lives better. AI Scientists work with various stakeholders to design, develop, and implement data-driven solutions. This position applies deep expertise in advanced analytical tools such as generative AI, machine learning, deep learning, optimization, and statistical modeling to solve complex, high-impact business problems in the healthcare payer domain.
As a Senior II AI Scientist, you will serve as a technical leader and strategic advisor, driving innovation across multiple business areas such as clinical care delivery, customer experience, and payment integrity. This is a hands-on technical leadership role &ndash; you will personally architect and build sophisticated AI solutions while simultaneously mentoring junior team members and influencing the technical direction of our AI initiatives. You will lead by example, writing production-quality code, conducting rigorous experiments, and demonstrating best practices in every aspect of AI development. This role requires not only mastery of generative AI, machine learning, and deep learning, but also strong architectural thinking, advanced software engineering capabilities, and the ability to translate ambiguous business challenges into innovative AI solutions.
You will be expected to remain deeply technical, actively contributing code, developing models, and solving complex technical problems alongside your team. Your leadership will come through the quality of your technical work, your ability to tackle the most challenging problems, and your commitment to elevating the skills and capabilities of those around you.
AI Scientists work closely with AI team members in the Product and Engineering tracks to collaboratively develop and deliver models and data-driven products. At the Senior II level, you will lead cross-functional initiatives, establish best practices through your own exemplary work, and serve as a subject matter expert to both technical and business stakeholders &ndash; all in service of making our members' health journeys easier.
If you're an accomplished AI Scientist with a proven track record of delivering impactful solutions through hands-on technical excellence and leading others through example in the healthcare industry, apply for this exciting opportunity today!
What You Bring to Cambia:
Qualifications:
The AI Scientist Sr II would have a degree (masters or PhD preferred) in a strongly a strongly quantitative field such as Computer Science, Statistics, Applied Mathematics, Physics, Operations Research, Bioinformatics, or Econometrics, and typically at least 12 years of related work experience. Equivalent combination of education and experience will be considered.
Skills and Attributes:
Technical Leadership &amp; Strategy
<ul><li>Recognized expert in generative AI, machine learning, and data science with ability to architect complex, novel solutions and define technical vision aligned with business strategy
</li><li>Deep understanding of the healthcare industry (preferred) with ability to identify and prioritize high-value AI opportunities, evaluate emerging technologies, and lead multiple complex projects from conception to production
</li></ul>Advanced Technical Expertise:
<ul><li>Mastery of advanced AI/ML techniques with ability to innovate beyond existing patterns, combined with expert-level Python programming and strong software engineering principles (design patterns, testing, CI/CD)
</li><li>Deep expertise in working with complex, real-world data challenges (noisy, high-dimensional, sparse, imbalanced, biased) across multiple data domains (e.g., claims, clinical, member engagement)
</li><li>Deep expertise in multiple AI modeling techniques with ability to select and combine methods innovatively, design scalable architectures for offline and online systems, and implement MLOps, model governance, and responsible AI practices
</li><li>Advanced SQL and data engineering skills, including optimization of complex queries and data pipeline design
</li></ul>Problem Solving &amp; Innovation:
<ul><li>Ability to tackle ambiguous, ill-defined problems and structure them into actionable AI initiatives that create measurable business value
</li><li>Proactive identification of AI opportunities for strategic advantage, with ability to anticipate technical risks, design mitigation strategies, and conduct research and experimentation including A/B testing and causal inference
</li></ul>Leadership &amp; Collaboration:
<ul><li>Proven ability to mentor and develop junior AI Scientists while establishing and evangelizing best practices, coding standards, and technical processes
</li><li>Strong leadership presence with ability to influence technical decisions across the organization, lead cross-functional teams, manage stakeholder relationships, and build productive partnerships across departments
</li><li>Excellent communication skills with ability to present complex technical concepts to audiences ranging from technical teams to C-level executives
</li></ul>Business Acumen:
<ul><li>Strong ability to translate business strategy into AI opportunities and technical requirements, quantify business impact and ROI of AI initiatives, and balance technical excellence with pragmatic business delivery
</li><li>Understanding of healthcare payer operations, regulations, and industry trends
</li></ul>C ore Knowledge:
Generative AI
<ul><li>Foundation Models &amp; Architectures: Deep understanding of transformer architectures, attention mechanisms, scaling laws, and experience with multiple model families (GPT, BERT, etc.)
</li><li>Advanced Fine-tuning &amp; Prompt Engineering: Expertise in parameter-efficient fine-tuning (LoRA, QLoRA, Adapters), instruction tuning, domain adaptation, and advanced prompting techniques (chain-of-thought, tree-of-thought, meta-prompting)
</li><li>RAG &amp; Agent Systems: Advanced RAG architectures, hybrid search strategies, knowledge base optimization, and experience designing AI agent systems with tool use, planning, and multi-agent collaboration
</li><li>Evaluation, Alignment &amp; Production: Deep expertise in evaluation methodologies (automated metrics, LLM-as-judge, human evaluation), alignment techniques (RLHF, DPO, constitutional AI), inference optimization, caching strategies, and cost management
</li><li>Multimodal &amp; Responsible AI: Experience with vision-language models and multimodal understanding, plus deep understanding of bias detection and mitigation, hallucination reduction, safety considerations, and privacy-preserving techniques
</li><li>Frameworks &amp; Tools: Expert-level proficiency with Hugging Face ecosystem, LangChain, LlamaIndex, vector databases, and emerging GenAI tools
</li></ul>Machine Learning
<ul><li>Advanced Algorithms &amp; Methods: Deep expertise across supervised, unsupervised, semi-supervised, and reinforcement learning paradigms, including ensemble methods (boosting, bagging, stacking), time series forecasting, and causal inference
</li><li>Optimization &amp; Evaluation: Deep understanding of optimization algorithms, convergence properties, custom loss function design, experimental design, statistical testing, and bias-variance tradeoff analysis
</li><li>AutoML &amp; Transfer Learning: Experience with automated model selection, hyperparameter optimization at scale, and advanced techniques for knowledge transfer and few-shot learning
</li></ul>Deep Learning
<ul><li>Advanced Architectures &amp; Optimization: Deep understanding of CNNs, RNNs, LSTMs, Transformers, GANs, VAEs, and diffusion models, plus advanced optimization methods, learning rate scheduling, and convergence analysis
</li><li>Regularization &amp; Specialized Domains: Advanced techniques including dropout variants, batch normalization, layer normalization, and architectural regularization, with expertise in NLP, computer vision, or speech processing
</li><li>Model Compression: Knowledge of quantization, pruning, distillation, and efficient inference techniques
</li></ul>Mathematics
<ul><li>Core Mathematical Foundations: Advanced linear algebra (matrix decompositions, eigen analysis, numerical methods), probability and statistics (Bayesian methods, hypothesis testing, experimental design), optimization theory (convex optimization, constrained optimization, stochastic optimization), and information theory
</li></ul>Data &amp; Software Engineering
<ul><li>Data Architecture &amp; SQL: Understanding of data warehousing, data lakes, modern data stack components, plus advanced SQL including query optimization, window functions, CTEs, and performance tuning
</li><li>Software Engineering &amp; MLOps: Design patterns, testing strategies (unit, integration, end-to-end), version control, CI/CD, model versioning, experiment tracking, model monitoring, and deployment strategies
</li><li>Distributed Computing &amp; Cloud: Experience with distributed training, data parallelism, scalable data processing (Spark, Dask, Ray), and proficiency with cloud AI/ML services (AWS SageMaker, Azure ML, GCP Vertex AI)
</li></ul>What you will do at Cambia:
Note: At the Senior II level, you are expected to demonstrate significant initiative, innovation, and leadership beyond core technical execution. You will shape technical direction, mentor others, and drive strategic AI initiatives.
Technical Leadership &amp; Architecture
<ul><li>Lead the design and architecture of complex, multi-component AI systems that solve strategic business problems, while defining technical standards, best practices, and design patterns for AI development across the team
</li><li>Evaluate and recommend new AI technologies, frameworks, and methodologies for adoption, serving as the technical authority on AI/ML topics
</li><li>Drive innovation by researching and prototyping cutting-edge AI techniques applicable to healthcare challenges, and lead technical design reviews to ensure high-quality solutions
</li></ul>Advanced Model Development &amp; Innovation
<ul><li>Research, design, and implement novel AI solutions using state-of-the-art generative AI, machine learning, and deep learning techniques to handle complex, real-world healthcare data challenges
</li><li>Design custom algorithms and modeling approaches when existing solutions are insufficient, and develop advanced evaluation frameworks that capture business value and model behavior
</li><li>Create reusable components, libraries, and frameworks that accelerate AI development, and lead the development of production grade AI systems with robust monitoring, governance, and maintenance strategies
</li></ul>Strategic Problem Solving &amp; Business Impact
<ul><li>Partner with business leaders to identify high-impact AI opportunities and translate ambiguous business challenges into well-defined AI problems with clear success criteria
</li><li>Design comprehensive experimentation strategies including A/B testing, causal inference, and statistical validation
</li><li>Proactively identify risks, biases, and ethical considerations in AI solutions and develop mitigation strategies, while quantifying and communicating business impact and ROI to executive stakeholders
</li></ul>Data &amp; Engineering Excellence
<ul><li>Design and optimize complex data pipelines for model training, evaluation, and serving, while developing advanced feature engineering strategies that unlock model performance
</li><li>Build scalable, maintainable AI systems using modern MLOps practices and cloud infrastructure, with comprehensive monitoring and observability for production systems
</li><li>Ensure data quality, governance, and compliance with healthcare regulations (HIPAA, etc.)
</li></ul>Mentorship &amp; Team Development
<ul><li>Mentor junior and mid-level AI Scientists, providing technical guidance and career development support through code reviews and constructive feedback
</li><li>Lead knowledge-sharing sessions, workshops, and technical presentations, while contributing to hiring and onboarding processes
</li><li>Foster a culture of continuous learning, experimentation, and technical excellence
</li></ul>Cross-Functional Collaboration &amp; Communication
<ul><li>Lead cross-functional initiatives involving Product, Engineering, and Business stakeholders, communicating complex technical concepts effectively to both technical and non-technical audiences, including executives
</li><li>Build strong partnerships across the organization to identify opportunities and remove blockers, represent the AI team in strategic planning and roadmap discussions, and contribute to thought leadership through presentations, publications, or industry engagement
</li></ul>Responsible AI &amp; Governance
<ul><li>Champion responsible AI practices including fairness, transparency, and accountability, while developing frameworks for bias detection, mitigation, and ongoing monitoring
</li><li>Ensure AI solutions comply with regulatory requirements and ethical guidelines, and lead efforts to document model decisions, assumptions, and limitations for governance purposes
 </li></ul></div><div>Pay ranges vary based on the candidate's work location. The expected hiring range depends on skills, experience, education, and training; relevant licensure / certifications; and performance history. 
</div><div><ul><li>Oregon, Washington, Utah, and Idaho: The expected hiring range is $168,000 - $ 211,000, the full salary range is $168,000 - $211,000, and the bonus target is 20% .
</li></ul></div><div><ul><li>North Dakota: The expected hiring range is $148K - $196K, and the full salary range is $148K - $244K.
</li></ul></div>About Cambia 
 
Working at Cambia means being part of a purpose-driven, award-winning culture built on trust and innovation anchored in our 100+ year history. Our caring and supportive colleagues are some of the best and brightest in the industry, innovating together toward sustainable, person-focused health care. Whether we're helping members, lending a hand to a colleague or volunteering in our communities, our compassion, empathy and team spirit always shine through. 
 
Why Join the Cambia Team? 
 
At Cambia, you can:
<ul><li>Work alongside diverse teams building cutting-edge solutions to transform health care.
</li><li>Earn a competitive salary and enjoy generous benefits while doing work that changes lives.
</li><li>Grow your career with a company committed to helping you succeed.
</li><li>Give back to your community by participating in Cambia-supported outreach programs.
</li>Connect with colleagues who share similar interests and backgrounds through our employee resource groups. 
<li>
</li></ul> 
We believe a career at Cambia is more than just a paycheck &ndash; and your compensation should be too. Our compensation package includes competitive base pay as well as a market-leading 401(k) with a significant company match, bonus opportunities and more. 
 
In exchange for helping members live healthy lives, we offer benefits that empower you to do the same. Just a few highlights include: 
 
<ul><li>Medical, dental and vision coverage for employees and their eligible family members, including mental health benefits.
</li><li>Annual employer contribution to a health savings account.
</li><li>Generous paid time off varying by role and tenure in addition to 10 company-paid holidays.
</li><li>Market-leading retirement plan including a company match on employee 401(k) contributions, with a potential discretionary contribution based on company performance (no vesting period).
</li><li>Up to 12 weeks of paid parental time off (eligibility requires 12 months of continuous service with Cambia immediately preceding leave).
</li><li>Award-winning wellness programs that reward you for participation.
</li><li>Employee Assistance Fund for those in need.
</li>Commute and parking benefits. 
<li>
</li></ul> 
Learn more about our benefits . 
 
We are happy to offer work from home options for most of our roles. To take advantage of this flexible option, we require employees to have a wired internet connection that is not satellite or cellular and internet service with a minimum upload speed of 5Mb and a minimum download speed of 10 Mb. 
 
As part of our security requirements, new hires will need access to a personal mobile device to set up Multi-Factor Authentication (MFA) upon joining the company. MFA is an important layer of protection for accessing Cambia systems and is required for all employees.
<div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div>We are an Equal Opportunity employer dedicated to a drug and tobacco-free workplace. All qualified applicants will receive consideration for employment without regard to race, color, national origin, religion, age, sex, sexual orientation, gender identity, disability, protected veteran status or any other status protected by law. A background check is required.
If you need accommodation for any part of the application process because of a medical condition or disability, please email CambiaCareers@cambiahealth.com . Information about how Cambia Health Solutions collects, uses, and discloses information is available in our Privacy Policy .</div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div>

AI Scientist Senior II

<div><h2 class="jobSectionHeader">DESCRIPTION</h2>
The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through cutting-edge generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising. 
 
Key job responsibilities 
Participate in the Science hiring process as well as mentor other scientists - improving their skills, their knowledge of your solutions, and their ability to get things done. 
 
Identify and devise new video related solutions following a customer-obsessed scientific approach to address customer or business problems when the problem is ill-defined, needs to be framed, and new methodologies or paradigms need to be invented at the product level.
 
 
Articulate potential scientific challenges of ongoing or future customers&rsquo; needs or business problems, and present interventions to address them. 
 
Independently assess alternative video related technologies, driving evaluation and adoption of those that fit best
 
 
A day in the life 
As an Applied Scientist on the Sponsored Brands Video team, you will work with a team of talented and experienced engineers, scientists, and designers to help bring new products to market and ensure that our customers are delighted by what we create. The Sponsored Brands Video team is responsible for the design, development, and implementation of Sponsored Brands Video experiences worldwide. 
 
About the team 
The Sponsored Brands Video team within Sponsored Products and Brands creates relevant and engaging video experiences, connecting advertisers and shoppers. We are on a mission to make Amazon the best in class destination for shoppers to discover, engage and build affinity with brands, making shopping delightful, &amp; personal.<h2 class="jobSectionHeader">
BASIC QUALIFICATIONS</h2><ul><li>3+ years of building machine learning models for business application experience</li><li>PhD, or Master's degree and 6+ years of applied research experience</li><li>Experience programming in Java, C++, Python or related language</li><li>Experience with neural deep learning methods and machine learning</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.</li><li>Experience with large scale distributed systems such as Hadoop, Spark etc.</li></ul> 
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. 
 
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner. 
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life &amp; AD&amp;D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits. 
USA, WA, SEATTLE - 167,100.00 - 226,100.00 USD annually</div>

Applied Scientist III, Sponsored Products

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