product scientist

Apple

<p>This role sits at the intersection of health, technology, and human potential, shaping how ordinary people understand, manage, and improve their well-being. As Senior Clinical AI Product Scientist, you will help transform real-world health insights into foundation models that empower individuals to make meaningful, sustainable changes in their daily lives. Your work will not only guide the technical direction of groundbreaking health AI systems, it will advance a more supportive, accessible, and human-centered future for everyone seeking to live healthier.<br>
<br>
<b>Description</b><br>
<br>
The Senior Clinical AI Product Scientist in Health AI will serve as a pivotal leader in the intersection of clinical medicine, machine learning, and product development. You define and drive the technical and product requirements for next-generation foundational AI systems that serve healthcare providers, patients, caregivers, and consumers. Leveraging your deep product and technical experience in machine learning and , you will lead end-to-end development of health foundation models for medical record processing, clinical workflows, and patient-facing applications. You will conduct stakeholder research across clinical domains, architect AI systems in healthcare settings, define validation and evidence-generation frameworks, and make informed technical decisions from research through production deployment.&quot;,&quot;responsibilities&quot;:&quot;Lead cross-functional teams (data science, machine learning engineering, clinical informatics) to develop foundational AI systems in the healthcare domain.<br>
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Define product strategy and technical requirements novel AI health models and their application in user products and research.<br>
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Conduct user research and discovery with stakeholders (clinicians, informaticists, patients, caregivers) to identify real-world problems and translate them into actionable product and ML requirements..<br>
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Design and execute evaluation frameworks to ensure high reliability, regulatory compliance, and adoption of AI solutions in healthcare.<br>
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Mentor and lead teams: supervise ML scientists and engineers, provide technical leadership, ensure best practices in ML, product design, and usability.<br>
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Maintain thought leadership: represent the organization at conferences, publish or present work, track emerging trends in health AI / LLMs and drive innovation.<br>
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<b>Preferred Qualifications</b><br>
<br>
Advanced degree (e.g., M.S., Ph.D.) in Computer Science.<br>
<br>
Experience working with electronic health record (EHR) systems and clinical natural language processing (NLP) applications<br>
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Track record of developing and deploying foundational LLMs/AI models in consumer settings.<br>
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Experience designing and conducting evaluation.<br>
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Familiarity with product development, regulation, and privacy considerations, in the health/life sciences field.<br>
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Ability to thrive in fast-paced environment, deal with uncertainty, and adapt to new and changing requirements<br>
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Proven track record of contributing to diverse teams in a collaborative environment<br>
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A passion for building outstanding and innovative products. This position involves a wide variety of interdisciplinary skills<br>
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<b>Minimum Qualifications</b><br>
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Minimum of 10 years of experience in healthcare AI/ML or intelligent systems/ML with demonstrated expertise in ML, or large language models (LLMs), or foundation models in the healthcare domain.<br>
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Proven track record of leading machine learning project and taking AI systems from research through production deployment and adoption.<br>
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Demonstrated experience coordinating across multiple functional areas (data science, clinical informatics, engineering) to deliver complex AI products.<br>
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Bachelor&rsquo;s degree in Computer Science, or related area of study, or equivalent experience.<br>
<br>
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant .<br>
<br>
<b>Pay &amp; Benefits</b><br>
<br>
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $203,300 and $365,400, and your base pay will depend on your skills, qualifications, experience, and location.<br>
<br>
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits.<br>
<br>
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.</p>

Senior Clinical AI Product Scientist - Health AIML

Google

<div>
 <strong>
  Minimum qualifications:
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
  </li>
  <li>
   5 years of work experience with analysis applications (extracting insights, performing statistical analysis, or solving business problems), and coding (Python, R, SQL), or 2 years of work experience with a Master's degree.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Preferred qualifications:
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
  </li>
  <li>
   5 years of work experience with analysis applications (extracting insights, performing statistical analysis, or solving business problems), and coding (Python, R, SQL).
  </li>
  <li>
   Experience working as a Data Scientist on a traditional tech product team (e.g., Product Manager, Engineering, etc.).
  </li>
  <li>
   Experience with experimentation analysis on internet/digital products (e.g., A/B tests, holdbacks, etc.).
  </li>
  <li>
   Experience with growth analysis or reporting on a large internet/digital product.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  About The Job
  <br/>
  <br/>
 </strong>
 As a Data Scientist on the Discover Experiences team, you will support the broader growth initiatives on the Experience (user-facing) Product team. This includes a reporting/understanding function, where you become the expert on the state of Discover's Growth and progress against goals, including interpreting various launches and holdbacks along with organic growth trends. There is also a product-related component in which you will support the launch of growth initiatives such as bringing Discover to more surfaces.
 <br/>
 <br/>
 Discover is one of the largest feed products in the world and part of the broader Search organization at Google. The Discover Experiences team owns the user-facing elements of the Discover product including feed units and experience, growth, AI integration into feed and more.
 <br/>
 <br/>
 In Google Search, we're reimagining what it means to search for information &ndash; any way and anywhere. To do that, we need to solve complex engineering challenges and expand our infrastructure, while maintaining a universally accessible and useful experience that people around the world rely on. In joining the Search team, you'll have an opportunity to make an impact on billions of people globally.
 <br/>
 <br/>
 The US base salary range for this full-time position is $138,000-$198,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
 <br/>
 <br/>
 Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google .
 <br/>
 <br/>
 <strong>
  Responsibilities
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Understand and report on Discover growth, drivers of growth and launch/holdback analysis.
  </li>
  <li>
   Support surface expansion and broader Discover Growth initiatives including 'Minus One' on Android, app-driven growth and feed refresh.
  </li>
  <li>
   Articulate and size new growth opportunities for Discover.
  </li>
  <li>
   Understand the broader Discover Ecosystem (including how ranking, content and experience interact from the user's perspective).
  </li>
  <li>
   Work with cross-functional teams (e.g., Product Management, Engineering, UXR, Design) on launch analysis, product iteration, and impact quantification.
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form .
</div>


Product Data Scientist, Discover Experience

<div><h3 class="jobSectionHeader"><b>Minimum qualifications:</b></h3><ul>
<li>Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.<br>
</li>
<li>8 years of work experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL) (or 5 years of work experience with a Master's degree).</li></ul><br>
<h3 class="jobSectionHeader"><b>
Preferred qualifications:</b></h3><ul>
<li>Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.<br>
</li>
<li>8 years of work experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL).</li>
</ul><div><h2 class="jobSectionHeader"><b>About the job</b></h2><p>
In this role, you will join the Data Intelligence team in the AI Data organization to provide the human expert data that trains, assesses, and elevates the Gemini family of models. You will partner with team members to define standards for data excellence and develop intelligent systems that are safe, helpful, and capable.</p>
The US base salary range for this full-time position is $163,000-$237,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.<br>
<div></div><br>
<div>Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.</div></div><p></p><div><h2 class="jobSectionHeader"><b>
Responsibilities</b></h2><ul>
<li>Analyze post-training data for Large Language Models (LLMs), conduct loss pattern analysis, and evaluate data quality.</li>
<li>Manage data usage in the model evolution life-cycle, from model training and tuning to evaluation and the gathering of user interaction signals.</li>
<li>Manage data science problems related to AI models evaluation and training. Contribute to improve the efficiency, impact and quality of the human data collection pipeline.</li>
<li>Utilize AI models and tools as integral components for evaluating the quality and impact of human data on AI model performance.</li>
<li>Work cross-functionally with Research, Engineering, and Product teams (Cloud AI Data and DeepMind).</li>
</ul></div>Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.</div>

Senior Product Data Scientist, AI Data

Amazon.com

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><div>
About Sponsored Products and Brands<br>
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.<br>
<br>
About our team<br>
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.<br>
<br>
As an Applied Scientist on this team, you will:
<br>
<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><br>
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.<br>
<br>
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"><b><br>
BASIC QUALIFICATIONS</b></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"><b>
PREFERRED QUALIFICATIONS</b></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><br>
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.<br>
<br>
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.<p><br>
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.</p><br>
USA, NY, New York - 172,400.00 - 223,400.00 USD annually<br>
USA, VA, Arlington - 142,800.00 - 193,200.00 USD annually<br>
USA, WA, SEATTLE - 142,800.00 - 193,200.00 USD annually</div><p></p>

Applied Scientist, Sponsored Products

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><div>
The Sponsored Products and Brands (SPB) team at Amazon Ads is re-imagining the advertising landscape through state-of-the-art 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.<br>
<br>
Curious about our advertising solutions? Discover more about Sponsored Products and Sponsored Brands to see how we&rsquo;re helping businesses grow on Amazon.com and beyond!<br>
<br>
Key job responsibilities<br>
This role will be pivotal in redesigning how ads contribute to a personalized, relevant, and inspirational shopping experience, with the customer value proposition at the forefront. Key responsibilities include, but are not limited to:<br>
<br>
<ul><li>Contribute to the design and development of GenAI, deep learning, multi-objective optimization and/or reinforcement learning empowered solutions to transform ad retrieval, auctions, whole-page relevance, and/or bespoke shopping experiences.</li><li>Collaborate cross-functionally with other scientists, engineers, and product managers to bring scalable, production-ready science solutions to life.</li><li>Stay abreast of industry trends in GenAI, LLMs, and related disciplines, bringing fresh and innovative concepts, ideas, and prototypes to the organization.</li><li>Contribute to the enhancement of team&rsquo;s scientific and technical rigor by identifying and implementing best-in-class algorithms, methodologies, and infrastructure that enable rapid experimentation and scaling.</li><li>Mentor and grow junior scientists and engineers, cultivating a high-performing, collaborative, and intellectually curious team.</li></ul><br>
A day in the life<br>
As an Applied Scientist on the Sponsored Products and Brands Off-Search team, you will contribute to the development in Generative AI (GenAI) and Large Language Models (LLMs) to revolutionize our advertising flow, backend optimization, and frontend shopping experiences. This is a rare opportunity to redefine how ads are retrieved, allocated, and/or experienced&mdash;elevating them into personalized, contextually aware, and inspiring components of the customer journey. You will have the opportunity to fundamentally transform areas such as ad retrieval, ad allocation, whole-page relevance, and differentiated recommendations through the lens of GenAI. By building novel generative models grounded in both Amazon&rsquo;s rich data and the world&rsquo;s collective knowledge, your work will shape how customers engage with ads, discover products, and make purchasing decisions. If you are passionate about applying frontier AI to real-world problems with massive scale and impact, this is your opportunity to define the next chapter of advertising science.<br>
<br>
About the team<br>
The Off-Search team within Sponsored Products and Brands (SPB) is focused on building delightful ad experiences across various surfaces beyond Search on Amazon&mdash;such as product detail pages, the homepage, and store-in-store pages&mdash;to drive monetization. Our vision is to deliver highly personalized, context-aware advertising that adapts to individual shopper preferences, scales across diverse page types, remains relevant to seasonal and event-driven moments, and integrates seamlessly with organic recommendations such as new arrivals, basket-building content, and fast-delivery options. To execute this vision, we work in close partnership with Amazon Stores stakeholders to lead the expansion and growth of advertising across Amazon-owned and -operated pages beyond Search. We operate full stack&mdash;from backend ads-retail edge services, ads retrieval, and ad auctions to shopper-facing experiences&mdash;all designed to deliver meaningful value.</div><h2 class="jobSectionHeader"><b><br>
BASIC QUALIFICATIONS</b></h2><ul><li>PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience</li><li>3+ years of building models for business application experience</li><li>Experience programming in Java, C++, Python or related language</li><li>Strong foundation in GenAI, large language models, machine learning, deep learning, probabilistic modeling, and/or optimization.</li><li>Experience developing and deploying models in real-world production environments.</li></ul><h2 class="jobSectionHeader"><b>
PREFERRED QUALIFICATIONS</b></h2><ul><li>Proven expertise in Generative AI, foundation models, LLMs, and/or fine-tuning and customization for downstream tasks.</li><li>Hands-on experience in ads ranking, retrieval, recommendation systems, search, or personalization at web scale.</li><li>Deep understanding of multi-modal modeling, few-shot learning, retrieval-augmented generation (RAG), or reinforcement learning from human feedback (RLHF).</li><li>Experience with online experimentation, A/B testing frameworks, and metrics design for advertising or e-commerce.</li><li>Demonstrated ability to communicate complex technical topics clearly to both technical and non-technical audiences.</li><li>Experience in computational advertising, including familiarity with auction theory, ad economics, and advertiser performance metrics.</li></ul><br>
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.<br>
<br>
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.<p><br>
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.</p><br>
USA, NY, New York - 172,400.00 - 223,400.00 USD annually<br>
USA, WA, Seattle - 142,800.00 - 193,200.00 USD annually</div><p></p>

Applied Scientist, Off-Search Relevance, Sponsored Products

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><div>
The Sponsored Products and Brands (SPB) team at Amazon Ads is re-imagining the advertising landscape through generative and agentic 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 to transform every aspect of the advertising lifecycle; from ad creation, delivery, optimization, performance management, and beyond. We are a passionate group of innovators dedicated to developing state-of-the-art AI technologies that balance the needs of advertisers and enhance the shopping experience. Within SPB, the SPB Offsite (SPBO) 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 gen AI technologies to create better sponsored customer experiences off the store.<br>
<br>
The Principal Applied Scientist for SPBO leads the technical vision and scientific strategy for extending Amazon Advertising's sponsored experiences to the broader web&mdash;meeting shoppers wherever they search, browse, and discover products. This is a multi-disciplinary scientific space spanning machine learning, large-scale optimization, causal inference, NLP, information retrieval, and generative AI. You will define and drive the science roadmap for how Amazon connects advertisers with high-intent customers across third-party environments at massive scale and with low latency. As a GenAI-first organization, we build foundational and agentic models that power advertiser use cases across Ads, while empowering our Applied Scientists to directly build and ship products. You will be a hands-on technical leader who architects novel solutions end-to-end&mdash;from research through production&mdash;while mentoring a team of scientists across diverse domains.<br>
<br>
The problems you will tackle are among the hardest in ad tech. You will develop models that leverage Amazon's first-party shopping signals to reach high-value audiences in third-party environments where signal density differs fundamentally from on-Amazon contexts. You will innovate on real-time bidding, auction dynamics, and ranking models across heterogeneous supply sources with distinct inventory characteristics, latency constraints, and auction mechanics. You will design ML approaches that maintain effectiveness amid an evolving privacy landscape&mdash;turning constraints from cookie deprecation, regulation, and platform restrictions into innovation opportunities. You will influence attribution models that capture the incremental value of offsite advertising on shopping outcomes, bridging measurement gaps between offsite touchpoints and on-Amazon conversions. You will pioneer generative and agentic AI to personalize ad creatives and shopping experiences for offsite contexts, and develop scientific frameworks to optimize spend allocation across supply partners and channels.<br>
<br>
You will partner with engineering, product, and business leaders as well as external partners to shape product strategy with scientific insight and drive results at scale. You will represent Amazon Advertising's offsite science externally through patents and industry engagement.<br>
<br>
Key job responsibilities<br>
<ul><li>Driving the scientific vision of the teams in your organization and advising and influencing its technical leadership on ad serving, bidding, ranking, and offsite advertising models and products.</li></ul><br>
<ul><li>Identifying, tackling, and proposing innovative solutions to intrinsically hard, previously unsolved problems in offsite ad tech.
</li></ul><br>
<ul><li>Bringing clarity to complex problems, probing assumptions, illuminating pitfalls, fostering shared understanding, and guiding towards effective solutions.</li></ul><br>
<ul><li>Serving and being recognized by internal and external peers as a thought leader in offsite advertising science, including real-time bidding, personalization, privacy-preserving ML, and generative AI for ad experiences.
</li><li>Influencing your team's science and business strategy by driving one or more team roadmaps contributing to the organization's roadmap and taking responsibility for some organizational goals. You drive multiple new product features from inception to production launch.</li><li>Guiding the career development of others, actively mentoring and educating the larger applied science community on trends, technologies, and best practices.
</li></ul></div><h2 class="jobSectionHeader"><b>BASIC QUALIFICATIONS</b></h2><ul><li>5+ years of hands-on work in predictive modeling and analysis experience</li><li>PhD in Electrical Engineering, Computer Science, Mathematics, or a related technical field</li><li>Experience working in predictive modeling and analysis</li><li>Experience distilling informal customer requirements into problem definitions, dealing with ambiguity and competing objectives</li><li>Experience programming in Java, C++, Python or related language</li><li>Experience with leading experienced scientists as well as having a record of developing junior members from academia or industry to a career track in a business environment</li></ul><h2 class="jobSectionHeader"><b>
PREFERRED QUALIFICATIONS</b></h2><ul><li>10+ years of relevant work in industry or academia experience</li><li>Knowledge of problem solving, algorithm design and complexity analysis</li><li>Experience creating novel algorithms and advancing the state of the art</li><li>Have peer-reviewed scientific contributions in premier journals and conferences</li></ul><br>
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.<br>
<br>
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.<p><br>
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.</p><br>
USA, CA, Palo Alto - 228,700.00 - 309,400.00 USD annually<br>
USA, NY, New York - 218,800.00 - 295,900.00 USD annually<br>
USA, WA, Seattle - 198,900.00 - 269,000.00 USD annually</div><p></p>

Principal Applied Scientist, Amazon - Sponsored Products and Brands

Discovered MENA

<div>
 <p>
  💻
  <strong>
   Staff Data Scientist (Product Analytics)
  </strong>
 </p>
 <p>
  📍 Remote
 </p>
 <p>
  <br/>
 </p>
 <p>
  We&rsquo;re looking for a
  <strong>
   Staff Data Scientist (Product Analytics)
  </strong>
  to come in and
  <em>
   own product analytics end-to-end
  </em>
  with one of our clients. This is a high-impact role where you&rsquo;ll shape how data is used across the entire product lifecycle &mdash; from idea to launch and beyond.
 </p>
 <p>
  You&rsquo;ll be building a lot from the ground up 🚀 &mdash; setting up event tracking, defining experimentation frameworks, and making sure every product decision is backed by solid, reliable data.
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   What you&rsquo;ll be doing:
  </strong>
 </p>
 <ul>
  <li>
   Define and roll out event tracking standards across web, mobile, and backend
  </li>
  <li>
   Own and optimise key product funnels (onboarding, checkout, subscriptions, etc.)
  </li>
  <li>
   Build and scale an experimentation framework (A/B testing, guardrails, SRM checks, power analysis, MDE, etc.)
  </li>
  <li>
   Turn experiment results into clear, actionable insights
  </li>
  <li>
   Partner closely with Product &amp; Engineering to embed measurement into the dev lifecycle
  </li>
  <li>
   Deep-dive into product data (retention, adoption, segmentation) to guide roadmap decisions
  </li>
  <li>
   Work with Data Platform teams on data quality &amp; tooling
  </li>
  <li>
   Mentor analysts and help build a strong data culture 🧠
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Requirements:
  </strong>
 </p>
 <ul>
  <li>
   7+ years in product analytics / data science / applied stats
  </li>
  <li>
   Strong experience running A/B tests at scale (and understanding common pitfalls)
  </li>
  <li>
   Deep knowledge of event tracking &amp; instrumentation
  </li>
  <li>
   Advanced SQL + Python (pandas, scipy, statsmodels, etc.)
  </li>
  <li>
   Solid statistical foundation (hypothesis testing, power analysis, causal thinking)
  </li>
  <li>
   Experience defining product metrics (north star, guardrails, health metrics)
  </li>
  <li>
   Strong storytelling &amp; stakeholder communication skills
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Bonus points:
  </strong>
 </p>
 <ul>
  <li>
   If you speak Arabic
  </li>
  <li>
   Based in Saudi (Jeddah/Makkah) and experience in the GCC
  </li>
  <li>
   Background in e-commerce, marketplaces, or SaaS
  </li>
  <li>
   Experience with tools like Eppo, Statsig, LaunchDarkly, Optimizely
  </li>
  <li>
   Familiarity with Looker, Metabase, dbt, BigQuery, ClickHouse
  </li>
  <li>
   Exposure to Bayesian methods, sequential testing, or bandits
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   A bit more context:
  </strong>
 </p>
 <ul>
  <li>
   You&rsquo;ll be building the experimentation culture from scratch (an amazing opportunity to make your mark)
  </li>
  <li>
   This will start as an IC role, with strong potential to grow into leadership/management over time
  </li>
 </ul>
 <p>
 </p>
</div>


Staff Data Scientist 📍 Remote

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