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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

JPMorganChase

<div>JOB DESCRIPTION 
 
 
At JPMorgan Chase, AI and technology promote our global operations with unmatched scale and speed. We invest over $18 billion annually in innovation, data leverage, and security to shape the future for our clients, communities, and employees. The Chief Data &amp; Analytics Office (CDAO) accelerates our data and analytics journey, with the Machine Learning Center of Excellence (MLCOE) creating and deploying solutions for complex business challenges. By ensuring data quality and leveraging insights, the CDAO supports our commercial goals, enhancing productivity and risk management through AI and machine learning. The CDAO is also responsible for developing and implementing solutions that support the firm's commercial goals by harnessing artificial intelligence and machine learning technologies to develop new products, improve productivity, and enhance risk management effectively and responsibly.
As a Machine Learning Scientist &ndash; Natural Language Processing (NLP) - Senior Associate, you will own the full lifecycle of developing and deploying machine learning solutions, from ideation to production. Acting as a leading voice within JPMC on all things Generative AI (GenAI), you will partner closely with all lines of business to innovate new solutions that drive transformational change for the bank. You will actively participate in our knowledge sharing community, representing your work inside and outside of the firm at leading industry conferences amongst peers and leaders in the space. We seek someone who excels in a highly collaborative, fast-paced environment, and holds a strong passion for machine learning to make a significant impact at a leading global financial institution.
Job responsibilities
<ul><li>Research and develop state-of-the-art machine learning models to solve real-world problems and apply them to tasks involving Generative AI (GenAI)
</li><li>Act as a thought partner for JPMC leaders and help the business identify and implement new machine learning methods that deliver impact
</li><li>Drive cross-functional collaboration with multiple partner teams such as Business, Technology, Product Management, Legal, Compliance, Strategy, and Business Management to deploy solutions into production
</li><li>Lead firm-wide initiatives by developing large-scale frameworks to accelerate the application of machine learning models across different areas of the business
</li></ul>Required qualifications, capabilities, and skills
<ul><li>PhD in a quantitative discipline, e.g., Computer Science, Electrical Engineering, Mathematics, Operations Research, Optimization, or Data Science, OR an MS with at least 2 years of industry or research experience in the field
</li><li>Solid background in Generative AI (GenAI) and hands-on experience and solid understanding of machine learning and deep learning methods and toolkits (e.g., TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas)
</li><li>Ability to design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with business goals
</li><li>Scientific thinking with the ability to invent and to work both independently and in highly collaborative team environments
</li><li>Solid written and spoken communication to effectively communicate technical concepts and results to both technical and business audiences
</li></ul>Preferred qualifications, capabilities, and skills
<ul><li>Strong background in Mathematics and Statistics; Familiarity with the financial services industries and continuous integration models and unit test development
</li><li>Knowledge in search/ranking or Meta Learning
</li><li>Experience with A/B experimentation and data/metric-driven product development, cloud-native deployment in a large-scale distributed environment, and ability to develop and debug production-quality code
</li><li>Published research in areas of Machine Learning or Deep Learning at a major conference or journal
</li></ul>#MLCOE_jobs
#CDAO_CAO_jobs
ABOUT US 
 
 
<div><div>JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world's most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.
</div><div>We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.
<div>We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
JPMorgan Chase &amp; Co. is an Equal Opportunity Employer, including Disability/Veterans 
</div></div></div> 
 
ABOUT THE TEAM
 
 
Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we're setting our businesses, clients, customers and employees up for success.</div>

Machine Learning Scientist - Natural Language Processing (NLP) - Senior Associate - Machine Learning Center of Excellence

Data Scientist, Analytics (Ranking, AI)

Amazon.com

<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

New York University

<div>This position is based in New York and the selected candidate will be expected to work onsite as of their effective start date.
Assistant Research Scientist will:
<ul><li>Work on research on identifying how decision-making and behavioral flexibility differs across individuals, and how these arise from underlying neural processes
</li></ul><ul><li>Use machine learning and data analysis to characterize large-scale behavioral datasets from rodents trained on a decision-making task
</li></ul><ul><li>Help identify individual-specific behavioral strategies to link to the neural activity differences across those individuals
</li></ul><ul><li>Build standardized pipelines for the behavioral database and interpret the results under supervision
</li></ul><div>Approximately 10 hours per week 
</div><div></div><div>In compliance with NYC&rsquo;s Pay Transparency Act, the salary range for this position is $25/hr. New York University considers factors such as (but not limited to) the specific grant funding and the terms of the research grant when extending an offer. 
</div><div></div>We welcome applications from international candidates; however, please note that NYU is not an E-Verify employer and therefore unable to support STEM OPT extensions.</div>
 <div>Major in neuroscience or related field; h ave familiarity with data analysis and visualization in Python</div>
 <div>submit CV</div>
 <div>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>

Assistant Research Scientist Part Time Non-exempt (Savin Lab)

T-Mobile

<div>At T-Mobile, we invest in YOU! Our Total Rewards Package ensures that employees get the same big love we give our customers. All team members receive a competitive base salary and compensation package - this is Total Rewards. Employees enjoy multiple wealth-building opportunities through our annual stock grant, employee stock purchase plan, 401(k), and access to free, year-round money coaches. That&rsquo;s how we&rsquo;re UNSTOPPABLE for our employees!
At T-Mobile Advertising Solutions, we're building privacy-first advertising products powered by advanced machine learning, large-scale data processing, and cloud technologies. Our proprietary algorithms enable rich consumer insights, intelligent audience solutions, and measurable performance for advertisers while maintaining a strong commitment to consumer privacy. 
 
We are seeking a creative, and curious Senior Applied Scientist to join our team. In this role, you'll work at the intersection of machine learning, software engineering, and big data, building AI and ML systems that directly impact our customers and business. You'll collaborate with engineers, data scientists, product managers, and other stakeholders to solve complex problems and deliver innovative solutions at scale. 
 
We embrace Lean Development principles, iterative experimentation, continuous learning, and a strong build-measure-learn feedback culture. The work you do will directly shape the future of our products and technologies.<div><div><div><div><div><div><div><div><div>
Job Responsibilities:<ul><li>
Lead the end-to-end development of machine learning and data products aligned to business objectives, from problem framing through deployment and monitoring.</li><li>
Build scalable data, training, and inference pipelines using distributed processing and cloud technologies.</li><li>
Apply statistical methods, experimentation, and validation frameworks to ensure solution quality and business impact.</li><li>
Write production-quality code and contribute to engineering best practices, including testing, CI/CD, and observability.</li><li>
Collaborate across engineering, product, and business teams while leading other engineers and data scientists.
</li></ul>Education and Work Experience:<ul><li>
Bachelor's Degree plus 5 years of related work experience OR Advanced degree with 3 years of related experience (Required)</li><li>
Acceptable areas of study include Quantitative Discipline (math, statistics, economics, computer science, physics, engineering, etc.) (Required)</li><li>
4-7 years experience building and deploying machine learning and deep learning solutions at scale; familiarity with MLOps and DevOps practices and tools. (Required)</li><li>
4-7 years Experience working within big data architecture, modern analytical data platforms, and large-scale data warehousing technologies (e.g. BigQuery, Snowflake, Redshift) (Required)</li><li>
4-7 years Experience working with large-scale distributed data systems and cloud platforms (e.g. SQL, Python, Scala, AWS) (Required)</li><li>
4-7 years Experience solving complex data, machine learning, or algorithmic challenges in production environment using modern engineering practices.(Required)</li></ul> 
Knowledge, Skills and Abilities:<ul><li>
Strong background in AI/ML, data structures, statistical modeling, optimization algorithms, big data, and design thinking.</li><li>
Advanced knowledge of cloud-based services (GCP, AWS)
and Python, PySpark and related Python libraries (e.g. pandas, scikit-learn, scipy, numpy) for advanced data science tasks.</li><li>
Hands-on implementation and architectural familiarity with streaming data, relational and non-relational databases, and distributed processing technologies.</li><li>
Experience operating production machine learning and data systems in cloud and containerized environments.</li><li>
Experience in AdTech and GIS or geospatial data processing is a plus.</li></ul></div></div></div></div></div></div></div></div></div><ul><li>
At least 18 years of age</li><li>
Legally authorized to work in the United States</li></ul>
Travel: 
Travel Required (Yes/No): No 
 
DOT Regulated: 
DOT Regulated Position (Yes/No): No 
Safety Sensitive Position (Yes/No): No
Base Pay Range: $116,500 - $210,100
Corporate Bonus Target: 15%
The pay range above is the general base pay range for a successful candidate in the role. The successful candidate&rsquo;s actual pay will be based on various factors, such as work location, qualifications, and experience, so the actual starting pay will vary within this range.
At T-Mobile, employees in regular, non-temporary roles are eligible for an annual bonus or periodic sales incentive or bonus, based on their role. Most Corporate employees are eligible for a year-end bonus based on company and/or individual performance and which is set at a percentage of the employee&rsquo;s eligible earnings in the prior year. Certain positions in Customer Care are eligible for monthly bonuses based on individual and/or team performance. To find the pay range for this role based on hiring location, click here.
At T-Mobile, our benefits exemplify the spirit of One Team, Together! A big part of how we care for one another is working to ensure our benefits evolve to meet the needs of our team members. Full and part-time employees have access to the same benefits when eligible. We cover all of the bases, offering medical, dental and vision insurance, a flexible spending account, 401(k), employee stock grants, employee stock purchase plan, paid time off and up to 12 paid holidays - which total about 4 weeks for new full-time employees and about 2.5 weeks for new part-time employees annually - paid parental and family leave, family building benefits, back-up care, enhanced family support, childcare subsidy, tuition assistance, college coaching, short- and long-term disability, voluntary AD&amp;D coverage, voluntary accident coverage, voluntary life insurance, voluntary disability insurance, and voluntary long-term care insurance. We don't stop there - eligible employees can also receive mobile service &amp; home internet discounts, pet insurance, and access to commuter and transit programs! To learn about T-Mobile&rsquo;s amazing benefits, check out www.t-mobilebenefits.com.
Never stop growing! 
As part of the T-Mobile team, you know the Un-carrier doesn&rsquo;t have a corporate ladder&ndash;it&rsquo;s more like a jungle gym of possibilities! We love helping our employees grow in their careers, because it&rsquo;s that shared drive to aim high that drives our business and our culture forward. By applying for this career opportunity, you&rsquo;re living our values while investing in your career growth&ndash;and we applaud it. You&rsquo;re unstoppable! 
 
T-Mobile USA, Inc. is an Equal Opportunity Employer. All decisions concerning the employment relationship will be made without regard to age, race, ethnicity, color, religion, creed, sex, sexual orientation, gender identity or expression, national origin, religious affiliation, marital status, citizenship status, veteran status, the presence of any physical or mental disability, or any other status or characteristic protected by federal, state, or local law. Discrimination, retaliation or harassment based upon any of these factors is wholly inconsistent with how we do business and will not be tolerated. 
 
Talent comes in all forms at the Un-carrier. If you are an individual with a disability and need reasonable accommodation at any point in the application or interview process, please let us know by emailing ApplicantAccommodation@t-mobile.com or calling 1-844-873-9500. Please note, this contact channel is not a means to apply for or inquire about a position and we are unable to respond to non-accommodation related requests.</div>

Senior Applied Scientist

<div>Company Description 
Sia is a next-generation, global management consulting group. Founded in 1999, we were born digital. Today our strategy and management capabilities are augmented by data science, enhanced by creativity and driven by responsibility. We&rsquo;re optimists for change and we help clients initiate, navigate and benefit from transformation. We believe optimism is a force multiplier, helping clients to mitigate downside and maximize opportunity. With expertise across a broad range of sectors and services, our 3,000 consultants serve clients worldwide from 48 locations in 19 countries. Our expertise delivers results. Our optimism transforms outcomes.
Sia&rsquo;s AI &amp; Data Business Unit is the powerhouse of our firm&rsquo;s innovation&mdash;merging cutting-edge Data Science, Generative AI, and advanced digital solutions to transform industries. With over 350 experts worldwide, we tackle projects from proof-of-concept to large-scale deployment, always pushing the boundaries of AI capabilities. Our 12 R&amp;D labs in Europe and North America drive continuous research in areas like computer vision, MLOps, and deep learning, partnering closely with our business consultants for real-world impact. By joining Sia&rsquo;s AI &amp; Data team, you&rsquo;ll step into a vibrant, collaborative environment that nurtures professional growth and empowers you to shape the future of AI-driven consulting. 
Job Description 
To support its growth, Sia is recruiting a Data Scientist Consultant with a strong interest in Risk, Compliance and Regulatory topics and challenges.
Reporting to Sia's Data Science teams, your role is to support our clients' operational teams and compliance departments in defining their data needs, analyzing their data, deploying data science algorithms, and AI agents and providing strategic decision support.
These engagements require the implementation of complex analyses to support our clients, notably in:<ul><li>
Forward-Deployed Engineering</li><li>
Generative AI, Machine Learning &amp; Statistics</li><li>
Data Analysis for strategic support</li><li>
Data Engineering &amp; DevOps</li><li>
Data Transformation &amp; Acculturation</li></ul>
A few examples of engagements:<ul><li>
Predictive compliance risk monitoring: Building automated data pipelines and dashboards to track operational metrics and forecast the future health of compliance workstreams, enabling proactive risk identification and mitigation.</li><li>
AI-powered regulatory intelligence: Designing and deploying a GenAI-driven system that monitors regulatory change in real time, structures obligations, maps them automatically to internal policies and controls, scores compliance gaps, and orchestrates remediation workflows - all with a full source-of-truth audit trail for compliance, risk, and legal teams.</li><li>
Analytics/ML models for AML compliance: Built and refined ML models to automate due diligence and ID verification workflows, reducing manual review time. Managed third-party data integration and collaborated with Legal and Engineering to ensure compliant deployment.</li></ul>
As part of the firm's internal activities, your contribution will focus on the following areas:<ul><li>
Developing or strengthening our offerings through training, working groups, and internal/external materials.</li><li>
Our publication strategy (sector blogs, studies, press coverage). \</li><li>
Business development, by contributing to the definition of client needs and participating in sales activities.</li></ul>
Key Responsibilities:<ul><li>
Partner with our clients' leadership teams, engineers, program managers, and data analysts to understand data needs.</li><li>
Identify, acquire, process, and explore relevant data sources.</li><li>
Analyze large amounts of structured and unstructured information to discover trends and patterns.</li><li>
Use your data analytics and data science expertise to derive valuable insights from datasets, and build predictive models and machine learning algorithms.</li><li>
Design, build, fine-tune, and deploy LLM-based systems using models such as GPT, Claude, Gemini, Llama, and Mistral.</li><li>
Develop GenAI-powered applications (self-managed and API-based) that meet real business needs and comply with applicable regulations (GDPR, EU AI Act, model licenses).</li><li>
Design and optimize prompting strategies (few-shot, Chain/Tree-of-Thought, ReAct, self-reflection, guardrails) to improve reliability and control.</li><li>
Communicate at scale through multiple mediums: presentations, dashboards, datasets, bots, and more.</li><li>
Propose solutions and strategies to business challenges.</li><li>
Collaborate with engineering and product development teams.</li><li>
Work across a broad range of partners and projects, delivering models, algorithms, datasets, measurements, services, tools, and processes.</li></ul> 

Qualifications 
<ul><li>
Master's degree or Engineering degree (or equivalent) in Computer Science, Engineering, Data Science, or a related quantitative field.</li><li>
2+ years of experience as a Data Scientist or Data Analyst.</li><li>
Strong programming skills, particularly Python and SQL.</li><li>
Proficiency in at least one major GenAI application framework (LangChain, LlamaIndex, etc.).</li><li>
Experience with cloud platforms (AWS, Azure, or GCP).</li><li>
Knowledge of both proprietary and open-source model ecosystems (OpenAI, Anthropic, Mistral AI, Hugging Face, etc.).</li><li>
Excellent communication skills, with the ability to explain complex technical concepts simply.</li></ul>
Preferred technical experience:<ul><li>
Experience building agentic AI systems.</li><li>
Good understanding of machine learning techniques.</li><li>
Good understanding of statistical techniques and concepts.</li><li>
Experience with data visualization tools.</li><li>
Experience developing conversational AI systems / chatbots.</li><li>
Understanding of or experience with protocols and standards for connecting LLMs to external tools and databases, such as the Model Context Protocol (MCP).</li><li>
Experience deploying models at scale in production environments.</li></ul>
Preferred industry sector experiences<ul><li>
Regulatory Obligations Management: Analyze and document legal/regulatory requirements to maintain and update the client's RCM obligations library</li><li>
Control Design &amp; Implementation: Design and implement operational controls and compliance frameworks to ensure regulatory adherence</li><li>
Risk Assessment &amp; Testing: Lead RCSAs, thematic reviews, and control testing to identify compliance and operational gaps</li><li>
Regulatory Analysis &amp; Strategy: Interpret emerging regulatory trends and enforcement actions to inform compliance strategy</li><li>
Compliance Best Practices: Develop and maintain compliance best practices</li><li>
Regulatory Interpretation &amp; Controls Mapping: Interpret laws and regulations to assess applicability and map obligations to controls</li><li>
Risk &amp; Compliance Transformation: Support transformation engagements across first-line (controls design/testing) and second-line (risk, compliance) functions</li></ul> 

Additional Information 
Compensation &amp; Benefits
Sia invests in total rewards that support how our people work, live, and grow.
Compensation<ul><li>
Base Salary: $95,000-116,000. Actual compensation within this range will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by applicable law.</li><li>
Annual Performance Bonus</li></ul>
Benefits<ul><li>
Medical, dental, and vision; company-paid life and AD&amp;D; voluntary supplemental insurance and EAP</li><li>
401(k) with company match and immediate vesting; HSA and FSA options</li><li>
College savings and student loan repayment programs</li><li>
Paid parental leave; generous PTO, nine company holidays, and one floating holiday</li><li>
Cell phone stipend; well-being and professional development programs</li></ul>
Benefits are subject to applicable plan terms and eligibility requirements.
Workplace 
Sia values in-person collaboration. When serving clients, consultants may be required to work onsite at a client location based on engagement needs. Between client engagements, consultants are expected to work from a Sia office or approved coworking location at least three days per week. Candidates should reside within a reasonable commuting distance of a Sia office or approved coworking location. Sia maintains offices and coworking arrangements across multiple U.S. markets, including New York City, Charlotte, Greater Seattle, San Francisco Greater Bay Area, Los Angeles, Houston, Atlanta, Baltimore, Chicago, Washington D.C.
Work Authorization
Applicants must be legally authorized to work in the United States at the time of application and throughout their employment. This position is not eligible for employment visa sponsorship now or in the future.
Our Commitment
At Sia, we believe in fostering a diverse, equitable, and inclusive culture where our employees and partners are valued and thrive in a sense of belonging.<div></div>
Sia is an equal opportunity employer. All aspects of employment, including hiring, promotion, remuneration, or discipline, are based solely on performance, competence, conduct, or business needs.</div>

Consultant – Compliance Data Science & AI

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