aiml - applied ml engineer, data generation & verification

aiml - sr backend engineer, data and ml innovation

aiml - sr machine learning engineer, data and ml innovation

applied science manager , stores foundation ai (sfai)

applied science manager, sponsored products

category management project intern (tiktok shop - operation center) - 2026 start (bs/ms)

aiml - applied ml engineer, data generation & verification Jobs in Seattle

aiml - sr backend engineer, data and ml innovation Jobs in Seattle

aiml - sr machine learning engineer, data and ml innovation Jobs in Seattle

applied science manager , stores foundation ai (sfai) Jobs in Seattle

applied science manager, sponsored products Jobs in Seattle

data scientist product analytics

Data Scientist, Product Analytics

Amazon.com

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><div>
Amazon Music is an immersive audio entertainment service that deepens connections between fans, artists, and creators. From personalized music playlists to exclusive podcasts, concert livestreams to artist merch, Amazon Music is innovating at some of the most exciting intersections of music and culture. We offer experiences that serve all listeners with our different tiers of service: Prime members get access to all the music in shuffle mode, and top ad-free podcasts, included with their membership; customers can upgrade to Amazon Music Unlimited for unlimited, on-demand access to 100 million songs, including millions in HD, Ultra HD, and spatial audio; and anyone can listen for free by downloading the Amazon Music app or via Alexa-enabled devices. Join us for the opportunity to influence how Amazon Music engages fans, artists, and creators on a global scale.<br>
<br>
The Data, Insights, Science and Optimization, Consumer Product and Tech (DISCO CPT) team is looking for a Data Scientist to join a team of Data Scientists, Analytics Leads, Business Intelligence Engineers and Data Engineers who analyze big data, provide analytics and insights as well as build models and algorithms that power product for personalized experiences. The team focuses on accelerating Amazon Music customer growth by empowering Product teams to make sound, customer-centric decisions through data and insights. We build data pipelines, science models, self-service analytics, insights and dashboards, deliver engagement and retention at scale. In this role, you will pioneer and execute advanced analytics and experimentation efforts for the Amazon Music product team. You will work with stakeholders and partners to deliver experimentation insights, author scientific artifacts, build scalable models to advance our analytics and science products. The ideal candidate must be willing to effectively lead science solutions, prioritize across multiple stakeholders and projects and be ready to jump into a fast-paced, dynamic and fun environment.<br>
<br>
Key job responsibilities<br>
<ul><li>Data Scientist II on this role will be a thought partner to Product and Engineering organizations through their expertise in experimentation, statistical modeling and advanced analytics</li><li>Conceptualize and drive strategic growth areas: retention, voice + visual engagement, experimentation, Gen AI initiatives, and product excellence.</li><li>Bridge science, analytics, and engineering to deliver solutions informing strategic decisions on AM technology investments and long-term business performance</li><li>Drive experimentation, measurement efficiency tooling, and ROI tracking for AM leadership</li><li>Build and maintain causal models to understand customer sentiment and its impact on key engagement/retention metrics</li><li>Develop structural and predictive models using data science workflows to deliver measurable customer results</li></ul><br>
A day in the life<br>
<ul><li>Lead strategic initiatives across visual and voice experiences, experimentation and customer retention stakeholders</li><li>Conduct experimentation, build causal models to better understand key drivers for customer retention
</li><li>Evaluate existing metrics and lead deep dives to ensure the right measurement framework is leveraged to measure and enhance user adoption through visual and voice interfaces</li><li>Partner with product managers to translate business questions into actionable science projects</li><li>Influence product roadmaps through data-driven insights on customer behavior patterns</li><li>Identify and resolve customer experience friction points with cross-functional teams</li><li>Drive adoption of best practices and innovative solutions across the organization</li></ul></div><h2 class="jobSectionHeader"><b>
BASIC QUALIFICATIONS</b></h2><ul><li>Bachelor's degree</li><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>Experience applying theoretical models in an applied environment</li></ul><h2 class="jobSectionHeader"><b>
PREFERRED QUALIFICATIONS</b></h2><ul><li>Knowledge of machine learning concepts and their application to reasoning and problem-solving</li><li>Experience in Python, Perl, or another scripting language</li><li>Experience in defining and creating benchmarks for assessing GenAI model performance</li><li>Experience applying quantitative analysis to solve business problems and making data-driven business decisions</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>
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.<br>
<br>
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.<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, San Francisco - 157,300.00 - 212,800.00 USD annually<br>
USA, WA, Seattle - 136,000.00 - 184,000.00 USD annually</div><p></p>

Data Scientist, Amazon Music - DISCO

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><p>
WW Amazon Stores Finance Science (ASFS) works to leverage science and economics to drive improved financial results, foster data backed decisions, and embed science within Finance. ASFS is focused on developing products that empower controllership, improve business decisions and financial planning by understanding financial drivers, and innovate science capabilities for efficiency and scale.<br>
<br>
We are looking for a data scientist to lead high visibility initiatives for forecasting Amazon Stores' financials. You will develop new science-based forecasting methodologies and build scalable models to improve financial decision making and planning for senior leadership up to VP and SVP level. You will build new ML and statistical models from the ground up that aim to transform financial planning for Amazon Stores.<br>
<br>
We prize creative problem solvers with the ability to draw on an expansive methodological toolkit to transform financial decision-making with science. The ideal candidate combines data-science acumen with strong business judgment. You have versatile modeling skills and are comfortable owning and extracting insights from data. You are excited to learn from and alongside seasoned scientists, engineers, and business leaders. You are an excellent communicator and effectively translate technical findings into business action.<br>
<br>
Key job responsibilities<br>
<br>
Demonstrating thorough technical knowledge, effective exploratory data analysis, and model building using industry standard ML models<br>
Working with technical and non-technical stakeholders across every step of science project life cycle<br>
Collaborating with finance, product, data engineering, and software engineering teams to create production implementations for large-scale ML models<br>
Innovating by adapting new modeling techniques and procedures<br>
Presenting research results to our internal research community</p><h2 class="jobSectionHeader"><b>
BASIC QUALIFICATIONS</b></h2><ul><li>5+ 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>4+ years of data scientist experience</li><li>Experience with statistical models e.g. multinomial logistic regression</li><li>Bachelor's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science</li><li>Experience managing data pipelines</li></ul><h2 class="jobSectionHeader"><b>
PREFERRED QUALIFICATIONS</b></h2><ul><li>Experience as a leader and mentor on a data science team</li><li>Knowledge of AWS tech stack (e.g., AWS Redshift, S3, EC2, Glue)</li><li>Master's degree</li><li>Experience formulating and solving predictive modeling, machine learning, forecasting or statistical modeling problems</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>
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.<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, Sunnyvale - 183,000.00 - 247,600.00 USD annually<br>
USA, WA, Bellevue - 159,200.00 - 215,300.00 USD annually<br>
USA, WA, Seattle - 159,200.00 - 215,300.00 USD annually</div><p></p>

Senior Data Scientist, Amazon Stores Finance Science, Amazon Stores Finance Science

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><p>
WW Amazon Stores Finance Science (ASFS) works to leverage science and economics to drive improved financial results, foster data backed decisions, and embed science within Finance. ASFS is focused on developing products that empower controllership, improve business decisions and financial planning by understanding financial drivers, and innovate science capabilities for efficiency and scale.<br>
<br>
We are looking for a data scientist to lead high visibility initiatives for forecasting Amazon Stores' financials. You will develop new science-based forecasting methodologies and build scalable models to improve financial decision making and planning for senior leadership up to VP and SVP level. You will build new ML and statistical models from the ground up that aim to transform financial planning for Amazon Stores.<br>
<br>
We prize creative problem solvers with the ability to draw on an expansive methodological toolkit to transform financial decision-making with science. The ideal candidate combines data-science acumen with strong business judgment. You have versatile modeling skills and are comfortable owning and extracting insights from data. You are excited to learn from and alongside seasoned scientists, engineers, and business leaders. You are an excellent communicator and effectively translate technical findings into business action.<br>
<br>
Key job responsibilities<br>
<br>
Demonstrating thorough technical knowledge, effective exploratory data analysis, and model building using industry standard ML models<br>
Working with technical and non-technical stakeholders across every step of science project life cycle<br>
Collaborating with finance, product, data engineering, and software engineering teams to create production implementations for large-scale ML models<br>
Innovating by adapting new modeling techniques and procedures<br>
Presenting research results to our internal research community</p><h2 class="jobSectionHeader"><b>
BASIC QUALIFICATIONS</b></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>Experience applying theoretical models in an applied environment</li><li>Bachelor's degree</li></ul><h2 class="jobSectionHeader"><b>
PREFERRED QUALIFICATIONS</b></h2><ul><li>Experience in a ML or data scientist role with a large technology company</li><li>Experience working on multi-team, cross-disciplinary projects</li><li>Experience effectively communicating complex concepts through written and verbal communication</li><li>Master's degree</li><li>Experience formulating and solving predictive modeling, machine learning, forecasting or statistical modeling problems</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>
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.<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, Sunnyvale - 157,300.00 - 212,800.00 USD annually<br>
USA, WA, Bellevue - 136,000.00 - 184,000.00 USD annually<br>
USA, WA, Seattle - 136,000.00 - 184,000.00 USD annually</div><p></p>

Data Scientist II, Amazon Stores Finance Science

<div>
 As a Data Engineer at Meta, you will shape the future of people-facing and business-facing products we build across our entire family of applications (Facebook, Instagram, Messenger, WhatsApp, Reality Labs, Threads). Your technical skills and analytical mindset will be utilized designing and building some of the world's most extensive data sets, helping to craft experiences for billions of people and hundreds of millions of businesses worldwide.In this role, you will collaborate with software engineering, data science, and product management teams to design/build scalable data solutions across Meta to optimize growth, strategy, and user experience for our 3 billion plus users, as well as our internal employee community.You will be at the forefront of identifying and solving some of the most interesting data challenges at a scale few companies can match. By joining Meta, you will become part of a world-class data engineering community dedicated to skill development and career growth in data engineering and beyond.Data Engineering: You will guide teams by building optimal data artifacts (including datasets and visualizations) to address key questions. You will refine our systems, design logging solutions, and create scalable data models. Ensuring data security and quality, and with a strong focus on efficiency, you will suggest architecture and development approaches and data management standards to address complex analytical problems.Product leadership: You will use data to shape product development, identify new opportunities, and tackle upcoming challenges. You'll ensure our products add value for users and businesses, by prioritizing projects, and driving innovative solutions to respond to challenges or opportunities.Communication and influence: You won't simply present data, but tell data-driven stories. You will convince and influence your partners using clear insights and recommendations. You will build credibility through structure and clarity, and be a trusted strategic partner.
 <br/>
 <br/>
 Data Engineer, Product Analytics Responsibilities:
 <br/>
 <br/>
 <ul>
  <li>
   Conceptualize and own the data architecture for multiple large-scale projects, while evaluating design and operational cost-benefit tradeoffs within systems
  </li>
  <li>
   Create and contribute to frameworks that improve the efficacy of logging data, while working with data infrastructure to triage issues and resolve
  </li>
  <li>
   Collaborate with engineers, product managers, and data scientists to understand data needs, representing key data insights in a meaningful way
  </li>
  <li>
   Define and manage Service Level Agreements for all data sets in allocated areas of ownership
  </li>
  <li>
   Determine and implement the security model based on privacy requirements, confirm safeguards are followed, address data quality issues, and evolve governance processes within allocated areas of ownership
  </li>
  <li>
   Design, build, and launch collections of sophisticated data models and visualizations that support multiple use cases across different products or domains
  </li>
  <li>
   Solve our most challenging data integration problems, utilizing optimal Extract, Transform, Load (ETL) patterns, frameworks, query techniques, sourcing from structured and unstructured data sources
  </li>
  <li>
   Assist in owning existing processes running in production, optimizing complex code through advanced algorithmic concepts
  </li>
  <li>
   Optimize pipelines, dashboards, frameworks, and systems to facilitate easier development of data artifacts
  </li>
  <li>
   Influence product and cross-functional teams to identify data opportunities to drive impact
  </li>
  <li>
   Mentor team members by giving/receiving actionable feedback
   <br/>
   <br/>
  </li>
 </ul>
 Minimum Qualifications:
 <br/>
 <br/>
 <ul>
  <li>
   Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
  </li>
  <li>
   4+ years of experience where the primary responsibility involves working with data. This could include roles such as data analyst, data scientist, data engineer, or similar positions
  </li>
  <li>
   4+ years of experience with SQL, ETL, data modeling, and at least one programming language (e.g., Python, C++, C#, Scala, etc.)
   <br/>
   <br/>
  </li>
 </ul>
 Preferred Qualifications:
 <br/>
 <br/>
 <ul>
  <li>
   Master's or Ph.D degree in a STEM field
  </li>
  <li>
   Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
  </li>
  <li>
   Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
  </li>
  <li>
   Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
   <br/>
   <br/>
  </li>
 </ul>
 About Meta:
 <br/>
 <br/>
 Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today&mdash;beyond the constraints of screens, the limits of distance, and even the rules of physics.
 <br/>
 <br/>
 Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.
 <br/>
 <br/>
 Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at accommodations-ext@meta.com.
 <br/>
 <br/>
 $147,000/year to $208,000/year + bonus + equity + benefits
 <br/>
 <br/>
 Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about  benefits  at Meta.
</div>


Data Engineer, Product Analytics

Amazon Web Services

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></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.<br>
<br>
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.<br>
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.
<br>
<br>
Key job responsibilities<br>
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.<br>
Specific responsibilities include:<br>
<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><br>
About the team<br>
<br>
Why AWS?<br>
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.<br>
<br>
Inclusive Team Culture<br>
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.<br>
<br>
Mentorship &amp; Career Growth<br>
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.<br>
<br>
Work/Life Balance<br>
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.<br>
<br>
Hybrid Work<br>
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"><b>
BASIC QUALIFICATIONS</b></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"><b>
PREFERRED QUALIFICATIONS</b></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><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>
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.<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, Santa Clara - 157,300.00 - 212,800.00 USD annually<br>
USA, NY, New York - 153,400.00 - 207,500.00 USD annually<br>
USA, WA, Seattle - 136,000.00 - 184,000.00 USD annually</div><p></p>

Data Scientist, AWS Quick Data

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><p>
Amazon is investing heavily in building a world-class advertising business, and we are responsible for defining and delivering a collection of advertising tools and products that drive discovery and Advertiser success. Our products are strategically important to our Retail and Marketplace businesses, driving long-term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class products. We are highly motivated, collaborative, and fun-loving with an entrepreneurial spirit and bias for action.<br>
<br>
The Marketing Effectiveness &amp; Attribution Science team develops causal inference and machine learning systems to measure the impact of marketing programs across Amazon's advertising ecosystem. We build production-grade attribution models that help business teams understand what's working, optimize resource allocation, and drive advertiser growth. Our work sits at the intersection of econometrics, scalable ML systems, and high-stakes business decisions.<br>
<br>
As a Data Scientist on this team, you will own end-to-end modeling pipelines &mdash; from problem formulation and experimental design to model development, productionization, and stakeholder communication.<br>
<br>
Major responsibilities include:<br>
<br>
Translate / Interpret:<br>
<br>
Partner with cross-functional teams to translate business questions into rigorous causal inference problems<br>
Design observational studies and quasi-experiments to measure marketing effectiveness when traditional A/B tests are infeasible<br>
Work with data engineering to instrument new data pipelines when existing data cannot answer the causal question<br>
<br>
Measure / Quantify / Expand:<br>
<br>
Own and evolve production attribution models across multiple marketing channels<br>
Build and maintain causal inference pipelines using methods such as Difference-in-Differences, Synthetic Control, Double Machine Learning, and Media Mix Models<br>
Develop scalable PySpark and Python codebases that process large-scale event data<br>
Continuously improve model accuracy through feature engineering, heterogeneity analysis, and sensitivity testing<br>
<br>
Explore / Enlighten:<br>
<br>
Investigate anomalies in model outputs and deep-dive to identify root causes<br>
Develop automated data quality checks and model diagnostics<br>
Research and prototype next-generation measurement methods<br>
<br>
Make Decisions / Recommendations:<br>
<br>
Present findings to senior leadership with clear recommendations<br>
Build dashboards and self-service tools that enable stakeholders to explore results independently<br>
Write production-quality Python code for data analysis, model training, and result publishing</p><h2 class="jobSectionHeader"><b>
BASIC QUALIFICATIONS</b></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"><b>
PREFERRED QUALIFICATIONS</b></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><li>Knowledge of relevant statistical measures such as confidence intervals, significance of error measurements, development and evaluation data sets, etc.</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, WA, SEATTLE - 136,000.00 - 184,000.00 USD annually</div><p></p>

Data Scientist, Advertising, AMPI Measurement

Explore 265+ Data scientist product analytics in Seattle this May. Find roles across top companies and apply now to boost your career.