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machine learning scientist

Amazon.com

<div><h2 class="jobSectionHeader">DESCRIPTION</h2><div>
The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through industry leading 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. 
 
We are seeking an experienced Data Scientist to join the Sponsored Products Auction team. This team is responsible for building and evaluating mechanisms to rank and price billions of ad impressions per day. We're looking for a Data Scientist to define measures of auction efficiency and produce insights into the quality of inputs to our auction (supply, demand, ML model predictions). This role will also be responsible for exploratory data analysis to identify opportunities for improvement of the system and working closely with Economists, Applied Scientists and Engineers to improve our product. 
 
As a Data Scientist on this team, you will: 
<ul><li>Solve real-world problems by getting and analyzing large amounts of data, diving deep to identify business insights and opportunities, design simulations and experiments, developing statistical and ML models by tailoring to business needs, and collaborating with Scientists, Engineers, BIE's, and Product Managers.</li><li>Write code (Python, R, Scala, SQL, etc.) to obtain, manipulate, and analyze data
</li><li>Apply statistical and machine learning knowledge to specific business problems and data.</li><li>Build decision-making models and propose solution for the business problem you define.</li><li>Retrieve, synthesize, and present critical data in a format that is immediately useful to answering specific questions or improving system performance.</li><li>Analyze historical data to identify trends and support optimal decision making.</li><li>Formalize assumptions about how our systems are expected to work, create statistical definition of the outlier, and develop methods to systematically identify outliers. Work out why such examples are outliers and define if any actions needed.</li><li>Given anecdotes about anomalies or generate automatic scripts to define anomalies, deep dive to explain why they happen, and identify fixes.</li><li>Conduct written and verbal presentations to share insights to audiences of varying levels of technical sophistication.</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. 
 
Team video https://youtu.be/zD_6Lzw8raE</div><h2 class="jobSectionHeader">
BASIC QUALIFICATIONS</h2><ul><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>2+ years of data scientist experience</li><li>3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience</li><li>Bachelor's degree</li><li>Experience applying theoretical models in an applied environment</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>Experience in Python, Perl, or another scripting language</li><li>Experience in a ML or data scientist role with a large technology company</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 - 153,400.00 - 207,500.00 USD annually 
USA, WA, SEATTLE - 136,000.00 - 184,000.00 USD annually</div>

Data Scientist

Lyft

<div>
 At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.
 
 
 Lyft Ads is one of Lyft&rsquo;s newest and fastest-growing businesses, focused on building the world&rsquo;s largest transportation media network. Our mission is to help brands reach riders during key moments of their journey&mdash;before, during, and after a ride&mdash;by delivering meaningful, contextually relevant ad experiences. We operate at the intersection of mobility data, real-time decision systems, and AI-powered personalization, enabling advertisers to run high-impact campaigns with measurable outcomes.
 
 
 We are seeking an
 
 Algorithms Scientist
 
 to help build the next generation of ads relevance, targeting, optimization, and measurement algorithms that power the Lyft Ads platform. In this role, you will work across large-scale datasets and complex real-time systems to design, prototype, and deploy production-grade machine learning models. You&rsquo;ll collaborate closely with Engineering, Product, Data Science, and Sales to translate ambiguous business and advertiser needs into rigorous algorithmic solutions that improve ad performance, enhance marketplace efficiency, and drive meaningful revenue growth.
 
 
 This is a high-impact, highly technical role within a rapidly scaling business line. The ideal candidate brings strong applied machine learning intuition, hands-on modeling experience, and the ability to write clean, efficient production code. You will play a critical role in shaping how advertisers connect with Lyft riders&mdash;pushing the boundaries of personalization, measurement, and real-time optimization in a dynamic marketplace.
 
 
 Responsibilities:
 
 
 <ul>
 <li>
 Design, develop, and deploy production-grade machine learning models and algorithms that power core Lyft Ads capabilities, such as ad relevance, targeting, ranking, bid optimization, pacing, campaign delivery, and measurement.
 </li>
 <li>
 Own the end-to-end lifecycle of modeling projects &mdash; including problem definition, data exploration, feature engineering, model development, offline evaluation, deployment, and monitoring.
 </li>
 <li>
 Collaborate closely with Ads Engineering to integrate models into real-time ad-serving and batch decision systems, ensuring performance across latency, scalability, and reliability constraints.
 </li>
 <li>
 Analyze large-scale mobility, behavioral, and ads performance datasets to identify patterns, surface opportunities, and guide ML and AI driven product improvements.
 </li>
 <li>
 Implement rigorous model evaluation frameworks, including offline metrics, statistical tests, calibration, sensitivity analysis, and A/B experimentation to validate both model impact and system-level outcomes.
 </li>
 <li>
 Build robust training pipelines, feature transformations, and scoring infrastructure, ensuring reproducibility, observability, and long-term maintainability.
 </li>
 <li>
 Partner with Product, Engineering, and Sales to translate ambiguous advertiser goals (e.g., increased conversions, reach efficiency, brand lift) into measurable requirements and success metrics.
 </li>
 <li>
 Investigate and resolve model behavior issues, production regressions, calibration drift, and performance anomalies in close partnership with Ads Infra teams.
 </li>
 <li>
 Drive innovation by staying current with advances in ML for ranking, recommendation, causal inference, optimization, and ads measurement &mdash; and proactively identifying opportunities to apply them.
 </li>
 <li>
 Contribute to Lyft Ads&rsquo; modeling and experimentation infrastructure, through model cards, documentation, reproducibility standards, and code quality improvements.
 
 
 </li>
 </ul>
 Experience:
 
 
 <ul>
 <li>
 Master&rsquo;s, or PhD in Machine Learning, Computer Science, Statistics, Applied Mathematics, Engineering, or related quantitative fields; or equivalent applied industry experience.
 </li>
 <li>
 3&ndash;5 years of hands-on ML/applied science experience, ideally involving production models, large-scale systems, or ads/recommendation/relevance domains. Strong proficiency in Python and machine learning frameworks such as PyTorch, TensorFlow, JAX, or scikit-learn; ability to write clean, efficient, production-adjacent code.
 </li>
 <li>
 Experience working with large-scale datasets and distributed data tools (Spark, Snowflake, Presto, Databricks).
 </li>
 <li>
 Practical experience building and evaluating:
 </li>
 <ul>
 <li>
 Ranking and relevance models
 </li>
 <li>
 Optimization or pacing algorithms
 </li>
 <li>
 Predictive models for CTR, CVR, or user response
 </li>
 <li>
 Causal or experimentation-based measurement methods
 </li>
 </ul>
 <li>
 Understanding of online/offline evaluation techniques, including:
 </li>
 <ul>
 <li>
 Offline metrics (AUC, NDCG, MRR, calibration)
 </li>
 <li>
 A/B testing methodologies
 </li>
 <li>
 Bias correction and counterfactual estimation
 </li>
 </ul>
 <li>
 Ability to solve ambiguous problems by structuring analyses, evaluating trade-offs, and proposing algorithmic solutions grounded in scientific rigor.
 </li>
 <li>
 Strong communication skills, with an ability to clearly explain model behavior, constraints, trade-offs, and recommendations to engineering, product, and sales partners.
 </li>
 <li>
 Demonstrated ownership of modeling work, including debugging, monitoring, documentation, and iteration after deployment.
 </li>
 <li>
 Curiosity, initiative, and a track record of delivering measurable improvements through high-quality modeling.
 
 
 </li>
 </ul>
 
 Benefits:
 
 
 
 <ul>
 <li>
 Great medical, dental, and vision insurance options with additional programs available when enrolled
 </li>
 <li>
 Mental health benefits
 </li>
 <li>
 Family building benefits
 </li>
 <li>
 Child care and pet benefits
 </li>
 <li>
 401(k) plan to help save for your future
 </li>
 <li>
 In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team members have 15 days paid time off
 </li>
 <li>
 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible
 </li>
 <li>
 Subsidized commuter benefits
 </li>
 <li>
 Lyft Pink - Lyft team members get an exclusive opportunity to test new benefits of our Ridership Program
 
 
 </li>
 </ul>
 Lyft is an equal opportunity employer committed to an inclusive workplace that fosters belonging. All qualified applicants will receive consideration for employment without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, age, genetic information, or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law.
 
 
 Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule &mdash; Team Members will be expected to work in the office 3 days per week on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid
 
 
 The expected base pay range for this position in the New York City area is $128,000 - $160,000. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Range is not inclusive of potential equity offering, bonus or benefits. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.
 
 
 Total compensation is dependent on a variety of factors, including qualifications, experience, and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.
</div>

Data Scientist, Algorithms - Lyft Ads

Google

<div>Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Mountain View, CA, USA; New York, NY, USA.<h3 class="jobSectionHeader">
Minimum qualifications:</h3><ul>
<li>Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.</li>
<li>8 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 6 years of work experience with a PhD degree.</li></ul> 
<h3 class="jobSectionHeader">
Preferred qualifications:</h3><ul>
<li>10 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 8 years of work experience with a PhD degree.</li>
<li>Familiarity with modern Machine Learning and Large Language Model (LLM) techniques.</li>
<li>Ability to commit to knowledge and learning, respect for science, tolerance for ambiguity, and interest in practical application of science to business.</li>
<li>Excellent collaboration skills, with the ability to collaborate cross-functionally and work effectively with Data Scientist (DS), User Experience Researcher (UXR), product and engineering partners.</li>
</ul><div><h2 class="jobSectionHeader">About the job</h2>
In this role, you will partner cross-functionally to drive Google's mission of organizing the world&rsquo;s information and making it universally accessible and useful. As technology continues to evolve, your commitment remains to help users in their journey to connect to helpful information more easily, leveraging technology to find new ways to satisfy users' information needs. 
 
In this role, you will provide users with relevant and meaningful information based on their interests and understanding of the world&rsquo;s information. Your mission is to make it effortless for people to catch up on their interests by bringing together informative, entertaining content from the voices they care about. 
 
As a part of the Discover Data Science team, you will partner with cross-functional to drive that mission with a data-informed strategy, identifying opportunities and accelerating execution. As a part of the Discover Personalization and Quality team, you will partner with engineering and product, develop deep understanding of how to build a personalized retrieval and ranking system that delivers high-quality, compelling and valuable content. You will leverage a wide range of analysis tools (including metrics and AI raters, statistical modeling, cohort and exploratory analyses), and incorporate AI-driven understanding to define the job of a data scientist for the new era.The US base salary range for this full-time position is $207,000-$300,000 + 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.<div><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></div><div><h2 class="jobSectionHeader">
Responsibilities</h2><ul>
<li>Lead core understanding of retrieval and ranking ML systems and collaborate with engineers to deliver significant improvements that accelerate product growth.</li>
<li>Analyze systems to identify opportunities while maintaining end-to-end ownership of research agenda, execution, and insight delivery to leadership.</li>
<li>Build expertise in retrieval and ranking systems, advocating for changes, where needed, and driving cross-functional alignment.</li>
<li>Contribute as an individual contributor, as well as a Technical Lead for a small group of data scientists.</li>
<li>Manage ambiguous data science problems, and leveraging new technology to produce quantum leaps forward in understanding, such as via LLM-driven tooling.</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>

Staff Data Scientist, Discover Personalization and Quality

Amazon Web Services

<div><h2 class="jobSectionHeader">DESCRIPTION</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. 
 
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! 
 
Key job responsibilities 
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: 
 
<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> 
A day in the life 
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. 
 
About the team 
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"> 
BASIC QUALIFICATIONS</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">
PREFERRED QUALIFICATIONS</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> 
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, WA, Seattle - 142,800.00 - 193,200.00 USD annually</div>

Applied Scientist, Off-Search Relevance, Sponsored Products

Datadog

<div>
 As a Research Scientist on our team, you will partner with Research Engineers, working on fundamental research problems and collaborating with Datadog's product and engineering teams to translate research advances into products.
 
 
 Building on our track record of AI-powered solutions (e.g., Bits AI, Bits Evolve, and our time series foundation model), Datadog AI Research tackles high-risk, high-reward problems grounded in real-world challenges in cloud observability and security.
 
 
 We are focused on two research areas:
 
 
 <ul>
 <li>
 World Models for Observability -- Training multimodal foundation models that learn the joint dynamics of distributed systems across metrics, traces, logs, topology, and events. These models power advanced forecasting, anomaly detection, root cause analysis, counterfactual simulation ("what if?"), and provide a learned planning backbone for our autonomous agents.
 </li>
 <li>
 Trained Agents for Observability -- Post-training models to operate autonomously across Datadog's domain. SRE incident response is our first target, with a clear path to code repair, security response, and infrastructure optimization. We build the simulation environments, RL training loops, and evaluation infrastructure needed to train agents that match or surpass frontier models at a fraction of the cost.
 
 
 </li>
 </ul>
 
 What You'll Do:
 
 
 
 <ul>
 <li>
 Conduct research in generative AI and machine learning, building specialized foundation models and trained agents for observability
 </li>
 <li>
 Train multimodal models on large-scale, diverse telemetry data (metrics, logs, traces, topology, events) using distributed training infrastructure
 </li>
 <li>
 Design and build simulated environments and RL training loops for on-policy agent training and evaluation
 </li>
 <li>
 Collaborate with cross-functional teams (Product, Engineering) to integrate capabilities like multimodal world modeling and autonomous agents into Datadog's products
 </li>
 <li>
 Stay at the forefront of foundation models, world models, and RL-based agent research
 </li>
 <li>
 Contribute to research publications, present at top-tier conferences (e.g., NeurIPS, ICLR, ICML), and help open-source key model artifacts and benchmarks
 
 
 </li>
 </ul>
 
 Who You Are:
 
 
 
 <ul>
 <li>
 You hold a PhD in Computer Science, Machine Learning, or a related field, with deep expertise in areas like generative modeling, world models, AI agents, reinforcement learning, or multimodal learning (or have equivalent experience)
 </li>
 <li>
 You have extensive experience designing and implementing deep learning models and agents, with a strong background in distributed training frameworks (e.g., DeepSpeed, Megatron-LM) and ML libraries (PyTorch)
 </li>
 <li>
 You have a track record of impactful publications at top-tier venues (e.g., NeurIPS, ICLR, ICML, TMLR)
 </li>
 <li>
 You are familiar with efficient training, post-training, and inference techniques for large foundation models
 </li>
 <li>
 You can explain complex models and research findings to both technical and non-technical audiences
 
 
 </li>
 </ul>
 
 Bonus Points (any of the following):
 
 
 
 <ul>
 <li>
 Experience bridging research and real-world product applications, especially with large foundation models, world models, or RL-trained agents
 </li>
 <li>
 Passion for pushing the boundaries of AI with a focus on customer impact and scalable deployment
 </li>
 <li>
 Experience writing production data pipelines and applications
 </li>
 <li>
 Hands-on experience with GPU programming and optimization, including CUDA
 
 
 </li>
 </ul>
 
 Datadog values people from all walks of life. We understand not everyone will meet all the above qualifications on day one. That's okay. If you&rsquo;re passionate about technology and want to grow your skills, we encourage you to apply.
 
 
 
 
 Benefits and Growth:
 
 
 
 <ul>
 <li>
 Competitive global benefits
 </li>
 <li>
 New hire stock equity (RSUs) and employee stock purchase plan (ESPP)
 </li>
 <li>
 Opportunity to collaborate closely with colleagues across the Datadog offices in New York City and Paris
 </li>
 <li>
 Opportunity to attend and present at conferences and meetups
 </li>
 <li>
 Intra-departmental mentor and buddy program for in-house networking
 </li>
 <li>
 An inclusive company culture, ability to join our Community Guilds (Datadog employee resource groups)
 
 
 </li>
 </ul>
 
 Benefits and Growth listed above may vary based on the country of your employment and the nature of your employment with Datadog.
 
 
 
 
 About Datadog:
 
 
 
 Datadog (NASDAQ: DDOG) is a global SaaS business, delivering a rare combination of growth and profitability. We are on a mission to break down silos and solve complexity in the cloud age by enabling digital transformation, cloud migration, and infrastructure monitoring of our customers&rsquo; entire technology stacks. Built by engineers, for engineers, Datadog is used by organizations of all sizes across a wide range of industries. Together, we champion professional development, diversity of thought, innovation, and work excellence to empower continuous growth. Join the pack and become part of a collaborative, pragmatic, and thoughtful people-first community where we solve tough problems, take smart risks, and celebrate one another. Learn more about #DatadogLife on Instagram, LinkedIn, and Datadog Learning Center.
 
 
 
 Equal Opportunity at Datadog:
 
 
 
 Datadog is an Affirmative Action and Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. Here are our Candidate Legal Notices for your reference.
 
 
 
 Your Privacy:
 
 
 
 Any information you submit to Datadog as part of your application will be processed in accordance with Datadog&rsquo;s Applicant and Candidate Privacy Notice.
 
 
 Datadog offers a competitive salary and equity package, and may include variable compensation. Actual compensation is based on factors such as the candidate's skills, qualifications, and experience. In addition, Datadog offers a wide range of best in class, comprehensive and inclusive employee benefits for this role including healthcare, dental, parental planning, and mental health benefits, a 401(k) plan and match, paid time off, fitness reimbursements, and a discounted employee stock purchase plan.
 
 
 The reasonably estimated yearly salary for this role at Datadog is:
 
 
 $140,000&mdash;$400,000 USD
 
 
 
 About Datadog:
 
 
 
 Datadog (NASDAQ: DDOG) is a global SaaS business, delivering a rare combination of growth and profitability. We are on a mission to break down silos and solve complexity in the cloud age by enabling digital transformation, cloud migration, and infrastructure monitoring of our customers&rsquo; entire technology stacks. Built by engineers, for engineers, Datadog is used by organizations of all sizes across a wide range of industries. Together, we champion professional development, diversity of thought, innovation, and work excellence to empower continuous growth. Join the pack and become part of a collaborative, pragmatic, and thoughtful people-first community where we solve tough problems, take smart risks, and celebrate one another. Learn more about #DatadogLife on Instagram, LinkedIn, and Datadog Learning Center.
 
 
 
 Equal Opportunity at Datadog:
 
 
 
 Datadog is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and other characteristics protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. Here are our Candidate Legal Notices for your reference.
 
 
 Datadog endeavors to make our Careers Page accessible to all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process, please complete this form. This form is for accommodation requests only and cannot be used to inquire about the status of applications.
 
 
 
 Privacy and AI Guidelines:
 
 
 
 Any information you submit to Datadog as part of your application will be processed in accordance with Datadog&rsquo;s Applicant and Candidate Privacy Notice. For information on our AI policy, please visit Interviewing at Datadog AI Guidelines.
</div>

AI Research Scientist – Datadog AI Research (DAIR)

<div><h2 class="jobSectionHeader">DESCRIPTION</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. 
 
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. 
 
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! 
 
Key job responsibilities 
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: 
 
<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> 
A day in the life 
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. 
 
About the team 
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. 
 
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!</div><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. 
 
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, Palo Alto - 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, Sponsored Products Off-Search Sourcing

CVS Health

<div>We&rsquo;re building a world of health around every individual &mdash; shaping a more connected, convenient and compassionate health experience. At CVS Health&reg;, you&rsquo;ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger &ndash; helping to simplify health care one person, one family and one community at a time.
Position Summary<div>
The Lead Data Scientist will play a critical role in developing, scaling, and deploying best‑in‑class forecasting models that drive merchandising category forecasting and decision‑making. This role sits within a high‑impact data science team responsible for translating complex transactional and behavioral data into accurate, actionable forecasts that inform financial, labor, and promotional strategies.
The Lead Data Scientist will own end‑to‑end model development, from problem formulation and feature engineering through validation, deployment, and ongoing performance monitoring, while providing technical leadership and mentorship to other data scientists.</div> 
Required Qualifications<div><ul><li>
7+ years of professional experience in data science, applied statistics, or machine learning</li><li>
Hands‑on experience developing time series forecasting or predictive models in a production environment</li><li>
Proficiency in Python for data analysis and model development</li><li>
Experience working with SQL and large, structured datasets</li><li>
Demonstrated experience applying statistical or machine learning techniques (e.g., regression, tree‑based models, time series models)</li><li>
Experience deploying, maintaining, or operationalizing models in partnership with engineering or analytics teams</li><li>
Previous experience in a lead or senior individual contributor role, owning model design and technical decisions</li></ul></div> 
Preferred Qualifications<div><ul><li>
Strong problem‑solving skills with the ability to translate ambiguous business questions into well‑defined analytical problems</li><li>
Experience influencing stakeholders and communicating model insights to non‑technical audiences</li><li>
Background in finance, retail, or demand forecasting domains</li><li>
Experience mentoring junior data scientists or providing technical leadership across projects</li><li>
Familiarity with model monitoring, performance drift, and iterative model improvement</li><li>
Ability to balance statistical rigor with pragmatic business constraints and timelines</li></ul></div> 
Education
Bachelor&rsquo;s degree or equivalent work experience in Mathematics, Statistics, Computer Science, Analytics, Engineering, or a related discipline. 
Master&rsquo;s degree preferred.
Pay Range
The typical pay range for this role is:
$130,295.00 - $260,590.00 
This pay range represents the base hourly rate or base annual full-time salary for all positions in the job grade within which this position falls. The actual base salary offer will depend on a variety of factors including experience, education, geography and other relevant factors. This position is eligible for a CVS Health bonus, commission or short-term incentive program in addition to the base pay range listed above. This position also includes an award target in the company&rsquo;s equity award program. 
Our people fuel our future. Our teams reflect the customers, patients, members and communities we serve and we are committed to fostering a workplace where every colleague feels valued and that they belong.
Great benefits for great people
We take pride in offering a comprehensive and competitive mix of pay and benefits that reflects our commitment to our colleagues and their families. 
This full‑time position is eligible for a comprehensive benefits package designed to support the physical, emotional, and financial well‑being of colleagues and their families. The benefits for this position include medical, dental, and vision coverage, paid time off, retirement savings options, wellness programs, and other resources, based on eligibility. 
Additional details about available benefits are provided during the application process and on Benefits Moments. 
We anticipate the application window for this opening will close on: 05/31/2026
Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state and local laws.</div>

Lead Data Scientist - Retail Strategic Health Analytics

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