machine learning engineer, apple services engineering

2026 fall applied science internship - gen ai & large language models - united states, phd student science recruiting

2026 fall applied science internship - reinforcement learning & optimization (machine learning) - united states, phd student science recruiting

data scientist, product analytics Jobs in Seattle

data scientist, product analytics

machine learning engineer, apple services engineering Jobs in Seattle

senior data engineer

2026 fall applied science internship - gen ai & large language models - united states, phd student science recruiting Jobs in Seattle

2026 fall applied science internship - reinforcement learning & optimization (machine learning) - united states, phd student science recruiting Jobs in Seattle

machine learning scientist

Andiamo

<div>
 Data Scientist &ndash; Product &amp; AI
 
 
 
 About The Role
 
 
 
 We are looking for a
 
 Data Scientist
 
 to help solve complex, high-impact problems in product development and AI. You will work with
 
 large-scale, high-dimensional data sets
 
 , applying statistical methods, machine learning, and experimentation to guide product decisions and improve user experiences. Your insights will influence the direction of features, platforms, and strategies used by thousands of organizations.
 
 
 As a mid-level data scientist, you&rsquo;ll own projects end-to-end: defining success metrics, designing experiments, building predictive models, and communicating findings to cross-functional partners. You&rsquo;ll collaborate with product managers, engineers, and designers to turn raw data into actionable insights that drive measurable business and product outcomes.
 
 
 This role is a chance to move beyond dashboards&mdash;you&rsquo;ll uncover patterns, tell compelling stories with data, and contribute to building scalable data science practices that push the boundaries of what&rsquo;s possible.
 
 
 What You&rsquo;ll Do
 
 
 <ul>
 <li>
 Apply Analytical Methods: Use statistical modeling, machine learning, and data visualization to extract insights and guide product strategy.
 </li>
 <li>
 Experiment &amp; Learn: Design, run, and analyze A/B tests and other experiments to evaluate product changes and quantify impact.
 </li>
 <li>
 Build Predictive Models: Develop models that forecast user behavior, product performance, and key metrics.
 </li>
 <li>
 Define Success Metrics: Establish clear goals and KPIs that align product teams around measurable outcomes.
 </li>
 <li>
 Collaborate Across Teams: Partner with engineers, designers, and product leaders to ensure insights are translated into impactful features.
 </li>
 <li>
 Communicate Findings: Present results and recommendations to stakeholders, framing technical insights in clear, actionable terms.
 </li>
 <li>
 Contribute to Data Platforms: Work with engineering partners to improve data pipelines, instrumentation, and experimentation frameworks.
 
 
 </li>
 </ul>
 What We&rsquo;re Looking For
 
 
 <ul>
 <li>
 Professional Experience: Around 5 years of applied data science experience in product analytics, business intelligence, or machine learning.
 </li>
 <li>
 Programming Skills: Proficiency in SQL and Python (or R) for data manipulation, modeling, and analysis.
 </li>
 <li>
 Experimentation: Familiarity with experimental design, causal inference, and A/B testing at scale.
 </li>
 <li>
 Statistical Foundation: Strong grounding in probability, statistics, and data-driven problem solving.
 </li>
 <li>
 Communication: Ability to clearly present technical analyses to non-technical audiences and drive alignment on decisions.
 </li>
 <li>
 Education: Bachelor&rsquo;s degree in Statistics, Mathematics, Computer Science, Engineering, or related field; Master&rsquo;s degree a plus.
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 
 
 <ul>
 <li>
 Experience working with product teams or SaaS platforms.
 </li>
 <li>
 Knowledge of ML frameworks (scikit-learn, TensorFlow, or PyTorch) and data visualization tools (Tableau, Looker, or similar).
 </li>
 <li>
 Exposure to cloud data environments (AWS, GCP, or Azure).
 
 
 </li>
 </ul>
 ✨
 
 Why Join
 
 : This is your chance to tackle challenging data problems in AI and product development. You&rsquo;ll apply advanced methods, work with talented colleagues, and contribute to products that affect millions of users and billions of data points&mdash;all while growing your skills and career.
 
 
 
 About Andiamo
 
 
 
 Talent Partners for the AI Revolution. As a globally recognized staffing and consulting firm, we specialize in placing the top 2% of technology and go-to-market professionals with the world&rsquo;s largest and most well-known companies.
 
 
 For over 20 years, we've maintained the status of tier-one vendor for firms such as Palantir, Amazon, Fluidstack, Bloomberg, Relativity Space, Firefly, MasterCard, Visa, Two Sigma, Citadel, as well as other major financial services firms, elite hedge funds, Google-backed tech start-ups, and major software firms.
 
 
 Our talent solutions include Permanent Placement, Contract Staffing, Executive Search, and Dedicated Recruiting Services (RPO). Find out more at www.andiamogo.com
</div>

Data Scientist - Global Tech Leader

Amazon

<div>
 
 Description
 
 
 
 Are you passionate about solving unique customer-facing problems in the Amazon scale? Are you excited about utilizing statistical analysis, machine learning, data mining and leverage tons of Amazon data to learn and infer customer shopping patterns? Do you enjoy working with a diversity of engineers, machine learning scientists, product managers and user-experience designers? If so, you have found the right match!
 
 
 Fashion is extremely fast-moving, visual, subjective, and it presents numerous unique problem domains such as product recommendations, product discovery and evaluation. The vision for Amazon Fashion is to make Amazon the number one online shopping destination for Fashion customers by providing large selections, inspiring and accurate recommendations and customer experience.
 
 
 The NAS Shop and Keep (SHAKE) organization empowers customers to make confident, lasting purchase decisions by minimizing purchase anxiety and reducing returns. The NAS SHAKE science team advances this mission by innovating and developing scalable ML solutions tailored to these unique challenges. The team is hiring a Data Scientist who has a solid background in Statistical Analysis, Machine Learning and Data Mining and a proven record of effectively analyzing large complex heterogeneous datasets, and is motivated to grow professionally as a Data Scientist.
 
 
 Key job responsibilities
 
 
 <ul>
 <li>
 You will work on our Science team and partner closely with applied scientists, data engineers as well as product managers, UX designers, and business partners to answer complex problems via data analysis. Outputs from your analysis will directly help improve the performance of the ML based recommendation systems thereby enhancing the customer experience as well as inform the roadmap for science and the product.
 </li>
 <li>
 You can effectively analyze complex and disparate datasets collected from diverse sources to derive key insights, build segmentation models and improve customer experience by reducing retail returns.
 </li>
 <li>
 You have excellent communication skills to be able to work with cross-functional team members to understand key questions and earn the trust of senior leaders.
 </li>
 <li>
 You are able to multi-task between different tasks such as gap analysis of algorithm results, integrating multiple disparate datasets, doing business intelligence, analyzing engagement metrics or presenting to stakeholders.
 </li>
 <li>
 You thrive in an agile and fast-paced environment on highly visible projects and initiatives.
 
 
 </li>
 </ul>
 
 Basic Qualifications
 
 
 
 <ul>
 <li>
 1+ 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>
 2+ years of data/research scientist, statistician or quantitative analyst in an internet-based company with complex and big data sources experience
 </li>
 <li>
 1+ years of creating or contributing to mathematical textbooks, research papers, or educational content experience
 </li>
 <li>
 Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 
 
 <ul>
 <li>
 Ph.D. in Science, Technology, Engineering, or Mathematics (STEM)
 </li>
 <li>
 Knowledge of statistical packages and business intelligence tools such as SPSS, SAS, S-PLUS, or R
 </li>
 <li>
 Knowledge of machine learning concepts and their application to reasoning and problem-solving
 </li>
 <li>
 Experience with clustered data processing (e.g., Hadoop, Spark, Map-reduce, and Hive)
 </li>
 <li>
 Experience applying quantitative analysis to solve business problems and making data-driven business decisions
 </li>
 <li>
 Usage of generative AI tools to enhance workflow efficiency, with a willingness to learn effective prompting and evaluation practices.
 </li>
 <li>
 Ability to recognize opportunities where generative AI could enhance products, workflows, or customer experiences.
 
 
 </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 - 108,300.00 - 160,000.00 USD annually
 
 
 
 
 Company
 
 - Amazon.com Services LLC
 
 
 Job ID: A3206663
</div>

Data Scientist I, SHAKE

Amazon Web Services

<div><h2 class="jobSectionHeader">DESCRIPTION</h2><div>
Amazon Quick Suite is an enterprise AI platform that transforms how organizations work with their data and knowledge. Combining generative AI-powered search, deep research capabilities, intelligent agents and automations, and comprehensive business intelligence, Quick Suite serves tens of thousands of users. Our platform processes thousands of queries monthly, helping teams make faster, data-driven decisions while maintaining enterprise-grade security and governance. From natural language interactions with complex datasets to automated workflows and custom AI agents, Quick Suite is redefining workplace productivity at unprecedented scale. 
 
We are seeking a Data Scientist II to join our Quick Data team, focusing on evaluation and benchmarking data development for Quick Suite features, with particular emphasis on Research and other generative AI capabilities. Our mission is to engineer high-quality datasets that are essential to the success of Amazon Quick Suite. From human evaluations and Responsible AI safeguards to Retrieval-Augmented Generation and beyond, our work ensures that Generative AI is enterprise-ready, safe, and effective for users at scale. 
As part of our diverse team&mdash;including data scientists, engineers, language engineers, linguists, and program managers&mdash;you will collaborate closely with science, engineering, and product teams. We are driven by customer obsession and a commitment to excellence.
 
 
Key job responsibilities 
In this role, you will leverage data-centric AI principles to assess the impact of data on model performance and the broader machine learning pipeline. You will apply Generative AI techniques to evaluate how well our data represents human language and conduct experiments to measure downstream interactions. 
Specific responsibilities include: 
<ul><li>Design and develop comprehensive evaluation and benchmarking datasets for Quick Suite AI-powered features</li><li>Leverage LLMs for synthetic data corpora generation; data evaluation and quality assessment using LLM-as-a-judge settings</li><li>Create ground truth datasets with high-quality question-answer pairs across diverse domains and use cases</li><li>Lead human annotation initiatives and model evaluation audits to ensure data quality and relevance</li><li>Develop and refine annotation guidelines and quality frameworks for evaluation tasks</li><li>Conduct statistical analysis to measure model performance, identify failure patterns, and guide improvement strategies</li><li>Collaborate with ML scientists and engineers to translate evaluation insights into actionable product improvements</li><li>Build scalable data pipelines and tools to support continuous evaluation and benchmarking efforts</li><li>Contribute to Responsible AI initiatives by developing safety and fairness evaluation datasets</li></ul> 
About the team 
 
Why AWS? 
Amazon Web Services (AWS) is the world&rsquo;s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating &mdash; that&rsquo;s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. 
 
Inclusive Team Culture 
Here at AWS, it&rsquo;s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon conferences, inspire us to never stop embracing our uniqueness. 
 
Mentorship &amp; Career Growth 
We&rsquo;re continuously raising our performance bar as we strive to become Earth&rsquo;s Best Employer. That&rsquo;s why you&rsquo;ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. 
 
Work/Life Balance 
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there&rsquo;s nothing we can&rsquo;t achieve in the cloud. 
 
Hybrid Work 
We value innovation and recognize this sometimes requires uninterrupted time to focus on a build. We also value in-person collaboration and time spent face-to-face. Our team affords employees options to work in the office every day or in a flexible, hybrid work model near one of our U.S. Amazon offices.</div><h2 class="jobSectionHeader">
BASIC QUALIFICATIONS</h2><ul><li>2+ years of data scientist experience</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>1+ years of working with or evaluating AI systems experience</li><li>1+ years of creating or contributing to mathematical textbooks, research papers, or educational content experience</li><li>Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)</li><li>Experience applying theoretical models in an applied environment</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>Ph.D. in Science, Technology, Engineering, or Mathematics (STEM)</li><li>Knowledge of machine learning concepts and their application to reasoning and problem-solving</li><li>Experience in a ML or data scientist role with a large technology company</li><li>Experience in defining and creating benchmarks for assessing GenAI model performance</li><li>Experience working on multi-team, cross-disciplinary projects</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> 
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. 
 
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company&rsquo;s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. 
 
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, CA, Santa Clara - 157,300.00 - 212,800.00 USD annually 
USA, NY, New York - 153,400.00 - 207,500.00 USD annually 
USA, WA, Seattle - 136,000.00 - 184,000.00 USD annually</div>

Data Scientist, AWS Quick Data

Amazon.com

<div><h2 class="jobSectionHeader">DESCRIPTION</h2><div>
About Sponsored Products and Brands 
The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through 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. 
 
About our team 
The SPB Offsite team builds solutions to extend campaigns to reach customers off the store and extend shopping experiences on third party sites where shoppers search and discover products. We use industry leading machine learning, high scale low latency systems, and AI technologies to create better sponsored customer experiences off the store. This role will have deep interest in building the next innovations in ad tech and shopping wherever shoppers go. You will work with external and internal partners to connect ad tech systems, understand customers, and drive results at scale. You are a deeply technical leader who operates with a GenAI first approach to product, engineering, and science based solutions. 
 
As an Applied Scientist on this team, you will:
 
<ul><li>Drive end-to-end Machine Learning projects that have a high degree of ambiguity, scale, complexity.</li><li>Perform hands-on analysis and modeling of enormous data sets to develop insights that increase traffic monetization and merchandise sales, without compromising the shopper experience.</li><li>Build machine learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production; work closely with software engineers to assist in productionizing your ML models.</li><li>Run A/B experiments, gather data, and perform statistical analysis.</li><li>Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving.</li><li>Research new and innovative machine learning approaches.</li></ul> 
Why you will love this opportunity: Amazon is investing heavily in building a world-class advertising business. This team defines and delivers a collection of advertising products that drive discovery and sales. Our solutions generate billions in revenue and drive long-term growth for Amazon&rsquo;s Retail and Marketplace businesses. We deliver billions of ad impressions, millions of clicks daily, and break fresh ground to create world-class products. We are a highly motivated, collaborative, and fun-loving team with an entrepreneurial spirit - with a broad mandate to experiment and innovate. 
 
Impact and Career Growth: You will invent new experiences and influence customer-facing shopping experiences to help suppliers grow their retail business and the auction dynamics that leverage native advertising; this is your opportunity to work within the fastest-growing businesses across all of Amazon! Define a long-term science vision for our advertising business, driven from our customers' needs, translating that direction into specific plans for research and applied scientists, as well as engineering and product teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding.</div><h2 class="jobSectionHeader"> 
BASIC QUALIFICATIONS</h2><ul><li>3+ years of building models for business application experience</li><li>PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience</li><li>Experience programming in Java, C++, Python or related language</li><li>Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>Experience in professional software development</li><li>Experience in search advertising, search marketing, performance advertising, or similar digital advertising</li><li>Strong technical fluency in Generative AI</li><li>Deep understanding of large language models (LLMs), model fine tuning and prompt engineering</li><li>Ph.D. in computer science, mathematics, statistics, machine learning or equivalent quantitative field</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, NY, New York - 172,400.00 - 223,400.00 USD annually 
USA, VA, Arlington - 142,800.00 - 193,200.00 USD annually 
USA, WA, SEATTLE - 142,800.00 - 193,200.00 USD annually</div>

Applied Scientist, Sponsored Products

Data Scientist, Analytics (Technical Leadership)

<div><h2 class="jobSectionHeader">DESCRIPTION</h2><div>
Prime Video is a first-stop entertainment destination offering customers a vast collection of premium programming in one app available across thousands of devices. Prime members can customize their viewing experience and find their favorite movies, series, documentaries, and live sports &ndash; including Amazon MGM Studios-produced series and movies; licensed fan favorites; and programming from Prime Video add-on subscriptions such as Apple TV+, Max, Crunchyroll and MGM+. All customers, regardless of whether they have a Prime membership or not, can rent or buy titles via the Prime Video Store, and can enjoy even more content for free with ads. 
 
Are you interested in shaping the future of entertainment? Prime Video's technology teams are creating best-in-class digital video experience. 
 
As a Prime Video technologist, you&rsquo;ll have end-to-end ownership of the product, user experience, design, and technology required to deliver state-of-the-art experiences for our customers. You&rsquo;ll get to work on projects that are fast-paced, challenging, and varied. You&rsquo;ll also be able to experiment with new possibilities, take risks, and collaborate with remarkable people. 
 
We&rsquo;ll look for you to bring your diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. With global opportunities for talented technologists, you can decide where a career Prime Video Tech takes you! 
 
We are looking for a self-motivated, passionate and resourceful Applied Scientist to bring diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. You will spend your time as a hands-on machine learning practitioner and a research leader. You will play a key role on the team, building and guiding machine learning models from the ground up. At the end of the day, you will have the reward of seeing your contributions benefit millions of Amazon.com customers worldwide. 
 
Key job responsibilities 
<ul><li>Develop AI solutions for various Prime Video Recommendation and Personalization systems using Deep learning, GenAI, Reinforcement Learning, and optimization methods;</li><li>Work closely with engineers and product managers to design, implement and launch AI solutions end-to-end;</li><li>Design and conduct offline and online (A/B) experiments to evaluate proposed solutions based on in-depth data analyses;</li><li>Effectively communicate technical and non-technical ideas with teammates and stakeholders;</li><li>Stay up-to-date with advancements and the latest modeling techniques in the field;</li><li>Publish your research findings in top conferences and journals.</li></ul> 
A day in the life 
We're using advanced approaches such as foundation models to connect information about our videos and customers from a variety of information sources, acquiring and processing data sets on a scale that only a few companies in the world can match. This will enable us to recommend titles effectively, even when we don't have a large behavioral signal (to tackle the cold-start title problem). It will also allow us to find our customer's niche interests, helping them discover groups of titles that they didn't even know existed. We are looking for creative &amp; customer obsessed machine learning scientists who can apply the latest research, state of the art algorithms and ML to build highly scalable page personalization solutions. You'll be a research leader in the space and a hands-on ML practitioner, guiding and collaborating with talented teams of engineers and scientists and senior leaders in the Prime Video organization. You will also have the opportunity to publish your research at internal and external conferences.
 
 
About the team 
Prime Video Recommendation Science team owns science solution to power recommendation and personalization experience on various Prime Video surfaces and devices. We work closely with the engineering teams to launch our solutions in production.</div><h2 class="jobSectionHeader">
BASIC QUALIFICATIONS</h2><ul><li>PhD, or Master's degree and 6+ years of applied research experience</li><li>5+ years of building machine learning models for business application 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. 
 
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company&rsquo;s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. 
 
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, CA, Sunnyvale - 192,200.00 - 260,000.00 USD annually 
USA, NY, New York - 183,800.00 - 248,700.00 USD annually 
USA, WA, Seattle - 167,100.00 - 226,100.00 USD annually</div>

Sr. Applied Scientist, Prime Video - Personalization and Discovery Science

Opendoor

<div>
 
 Data Scientist, Pricing
 
 
 
 
 
 Location: Hyrbrid 4 onsite, 1 remote
 
 Seattle WA.
 
 
 
 Opendoor is transforming one of the largest, most complex markets in the world &mdash; residential real estate &mdash; using data at massive scale. Every pricing signal we generate directly impacts how we value homes, how we manage risk, and how efficiently capital moves through our marketplace. The work is highly leveraged: the quality of our pricing decisions influences conversion, margins, customer trust, and the company&rsquo;s financial performance.
 
 
 We are looking for mid to senior level Data Scientists. In this role, you will be a core driver of how Opendoor prices real estate at scale. You&rsquo;ll operate at the intersection of economics, machine learning, experimentation, and product strategy &mdash; tackling ambiguity, shaping the pricing roadmap, and building models/analyses that materially move the business. Your insights will influence how we evaluate millions of dollars of housing inventory &mdash; and directly shape outcomes for our customers, our balance sheet, and the health of our marketplace.
 
 
 
 What You&rsquo;ll Do
 
 
 
 
 <ul>
 <li>
 Build and maintain pricing metrics, dashboards, and frameworks.
 </li>
 <li>
 Run experiments and causal analyses to measure impact and drive decisions.
 </li>
 <li>
 Develop predictive + statistical models that improve pricing accuracy.
 </li>
 <li>
 Partner closely with Product, Engineering, and Operations teams to influence roadmap and model deployment.
 </li>
 <li>
 Deliver insights and narratives that inform executive strategy.
 
 
 
 </li>
 </ul>
 
 Skills &amp; Qualifications
 
 
 
 
 <ul>
 <li>
 Deep statistical reasoning: hypothesis design, experimental design, causal inference, and ability to distinguish signal vs noise.
 </li>
 <li>
 Proven end-to-end ML ownership: data acquisition, feature engineering, model development, validation, deployment, and ongoing monitoring.
 </li>
 <li>
 Strong SQL + Python proficiency; comfortable working with production data pipelines and modern ML tooling (e.g., Spark, Airflow, Ray, SageMaker, Vertex, etc.).
 </li>
 <li>
 Demonstrated ability to translate complex analytical findings into clear business recommendations and influence cross-functional decision-making.
 </li>
 <li>
 Experience working with ill-defined problems and driving clarity on problem definition, success metrics, and realistic tradeoffs.
 </li>
 <li>
 High data-quality bar: disciplined approach to validation, bias analysis, and making decisions rooted in evidence vs intuition.
 </li>
 <li>
 Effective communicator &mdash; able to tell the story behind the model to both highly technical and non-technical audiences.
 </li>
 <li>
 8+ years of experience in data science, product analytics, or a similar quantitative role.
 
 
 
 </li>
 </ul>
 
 Base salary range for this role varies. Generally, the base salary range is $186,000 &ndash; $256,000 annually + RSUs + ESPP + additional employee benefits (medical/dental/vision, life insurance, unlimited PTO, 401K).
 
 
 
 #
 
 
 At Opendoor our mission is to tilt the world in favor of homeowners and those who aim to become one. Homeownership matters. It's how people build wealth, stability, and community. It's how families put down roots, how neighborhoods strengthen, how the future gets built. We're building the modern system of homeownership giving people the freedom to buy and sell on their own terms. We&rsquo;ve built an end-to-end online experience that has already helped thousands of people and we&rsquo;re just getting started.
 
 
</div>

Data Scientist

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