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data analyst 2 - inventory audit & analytics - hybrid - seattle

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business analyst, wwgs business and customer analytics Jobs in Seattle

data analyst 2 - inventory audit & analytics - hybrid - seattle Jobs in Seattle

data analyst i

analytical data scientist

Data Scientist, Analytics (Technical Leadership)

<div>
 As a Data Scientist 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, Oculus). By applying your technical skills, analytical mindset, and product intuition to one of the richest data sets in the world, you will help define the experiences we build for billions of people and hundreds of millions of businesses around the world. You will collaborate on a wide array of product and business problems with a wide-range of cross-functional partners across Product, Engineering, Research, Data Engineering, Marketing, Sales, Finance and others. You will use data and analysis to identify and solve product development's biggest challenges. You will influence product strategy and investment decisions with data, be focused on impact, and collaborate with other teams. By joining Meta, you will become part of a world-class analytics community dedicated to skill development and career growth in analytics and beyond.Product leadership: You will use data to shape product development, quantify new opportunities, identify upcoming challenges, and ensure the products we build bring value to people, businesses, and Meta. You will help your partner teams prioritize what to build, set goals, and understand their product's ecosystem.Analytics: You will guide teams using data and insights. You will focus on developing hypotheses and employ a varied toolkit of rigorous analytical approaches, different methodologies, frameworks, and technical approaches to test them.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.
 
 
 Data Scientist, Product Analytics Responsibilities:
 
 
 <ul>
 <li>
 Work with large and complex data sets to solve a wide array of challenging problems using different analytical and statistical approaches
 </li>
 <li>
 Apply technical expertise with quantitative analysis, experimentation, data mining, and the presentation of data to develop strategies for our products that serve billions of people and hundreds of millions of businesses
 </li>
 <li>
 Identify and measure success of product efforts through goal setting, forecasting, and monitoring of key product metrics to understand trends
 </li>
 <li>
 Define, understand, and test opportunities and levers to improve the product, and drive roadmaps through your insights and recommendations
 </li>
 <li>
 Partner with Product, Engineering, and cross-functional teams to inform, influence, support, and execute product strategy and investment decisions
 
 
 </li>
 </ul>
 Minimum Qualifications:
 
 
 <ul>
 <li>
 Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
 </li>
 <li>
 Bachelor's degree in Mathematics, Statistics, a relevant technical field, or equivalent
 </li>
 <li>
 4+ years of work experience in analytics, data querying languages such as SQL, scripting languages such as Python, and/or statistical mathematical software such as R (minimum of 2 years with a Ph.D.)
 </li>
 <li>
 4+ years of experience solving analytical problems using quantitative approaches, understanding ecosystems, user behaviors &amp; long-term product trends, and leading data-driven projects from definition to execution [including defining metrics, experiment, design, communicating actionable insights]
 
 
 </li>
 </ul>
 Preferred Qualifications:
 
 
 <ul>
 <li>
 Master's or Ph.D. Degree in a quantitative 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
 
 
 </li>
 </ul>
 About Meta:
 
 
 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.
 
 
 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.
 
 
 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.
 
 
 $147,000/year to $208,000/year + bonus + equity + benefits
 
 
 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 Scientist, Product Analytics

<div>
 Meta&rsquo;s Products &amp; Applied Research (PAR) team is where product-focused research meets real-world impact, taking breakthrough AI research and transforming it into products that reach billions. As part of Meta Superintelligence Labs (MSL), we&rsquo;re driving the transformation of Meta&rsquo;s core experiences&mdash;across Facebook, Instagram, WhatsApp, Threads, and beyond&mdash;by applying cutting-edge research to real-world products at massive scale.We are looking for a Data Scientist to join our PAR organization where you will help define the experiences we build for billions of people and hundreds of millions of businesses around the world, by applying your technical skills, analytical mindset, and product intuition.In this role, you will collaborate on a wide array of product and business problems with a wide-range of cross-functional partners across Product, Engineering, Research, Data Engineering, Marketing, Sales, Finance and others.You will use data and analysis to identify and solve product development's biggest challenges. You will influence product strategy and investment decisions with data, be focused on impact, and collaborate with other teams. By joining Meta, you will become part of a world-class analytics community dedicated to skill development and career growth in analytics and beyond.Product leadership: You will use data to shape product development, quantify new opportunities, identify upcoming challenges, and ensure the products we build bring value to people, businesses, and Meta. You will help your partner teams prioritize what to build, set goals, and understand their product's ecosystem.Analytics: You will guide teams using data and insights. You will focus on developing hypotheses and employ a varied toolkit of rigorous analytical approaches, different methodologies, frameworks, and technical approaches to test them.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.
 
 
 Data Scientist, Products &amp; Applied Research Responsibilities:
 
 
 <ul>
 <li>
 Work with large and complex data sets to solve a wide array of challenging problems using different analytical and statistical approaches
 </li>
 <li>
 Apply technical expertise with quantitative analysis, experimentation, data mining, and the presentation of data to develop strategies for our products that serve billions of people and hundreds of millions of businesses
 </li>
 <li>
 Identify and measure success of product efforts through goal setting, forecasting, and monitoring of key product metrics to understand trends
 </li>
 <li>
 Define, understand, and test opportunities and levers to improve the product, and drive roadmaps through your insights and recommendations
 </li>
 <li>
 Partner with Product, Engineering, and cross-functional teams to inform, influence, support, and execute product strategy and investment decisions
 
 
 </li>
 </ul>
 Minimum Qualifications:
 
 
 <ul>
 <li>
 Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
 </li>
 <li>
 Bachelor's degree in Mathematics, Statistics, a relevant technical field, or equivalent practical experience
 </li>
 <li>
 A minimum of 6 years of work experience in analytics (minimum of 4 years with a Ph.D.)
 </li>
 <li>
 Experience with data querying languages (e.g. SQL), scripting languages (e.g. Python), and/or statistical/mathematical software (e.g. R)
 
 
 </li>
 </ul>
 Preferred Qualifications:
 
 
 <ul>
 <li>
 Master's or Ph.D. degree in a quantitative 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
 
 
 </li>
 </ul>
 About Meta:
 
 
 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.
 
 
 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.
 
 
 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.
 
 
 $177,000/year to $247,000/year + bonus + equity + benefits
 
 
 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 Scientist, Products & Applied Research

Capgemini

<div>
 
 
 Data Scientist
 
 
 
 Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you&rsquo;d like, where you&rsquo;ll be supported and inspired by a collaborative community of colleagues around the world, and where you&rsquo;ll be able to reimagine what&rsquo;s possible. Join us and help the world&rsquo;s leading organizations unlock the value of technology and build a more sustainable, more inclusive world.
 
 
 
 Job Description
 
 
 
 As a Data Scientist , you will lead the development and implementation of advanced data engineering solutions to support the deployment and optimization of Generative AI models. Your role will involve leveraging your extensive experience to design robust, scalable, and innovative data architectures that align with the unique requirements of General Artificial Intelligence (GenAI) applications.
 
 
 
 
 
 Key Responsibilities
 
 
 <ul>
 <li>
 The Machine Learning Engineer will be responsible for architectural design and planning, advanced data pipelines, model integration and optimization, scalability, performance and research and innovation supporting production generative AI systems.
 </li>
 <li>
 Production level ML workloads for customers using Databricks platform, including end-to-end ML pipelines, training/inference optimization, integration with cloud-native services and MLOps
 </li>
 <li>
 Build and maintain data engineering solutions on cloud platforms using hyperscaler services.
 </li>
 <li>
 Develop production-grade cloud (AWS/Azure/GCP) infrastructure that supports the deployment of ML applications, including drift monitoring
 </li>
 <li>
 Design, develop, and maintain data pipelines to efficiently collect, process, and load data from various sources into data storage systems (e.g., data warehouses, data lakes).
 </li>
 <li>
 Understanding indexing and vectorization to use with Generative AI prompt engineering.
 </li>
 <li>
 Strong understanding of fundamental data science concepts in NLP, including selection and understanding of embedding models.
 </li>
 <li>
 Use hyperscaler technologies to support data needs for expansion of Machine Learning/Data Science capabilities including generative AI.
 </li>
 <li>
 Design, develop, and implement scalable data pipelines and ETL/ELT processes using Python, PySpark and API integrations.
 </li>
 </ul>
 
 
 Required Skill and Experience
 
 
 
 
 <ul>
 <li>
 Bachelor's degree in computer science, data engineering, or a related field with 3+ year's experience (Master's preferred).
 </li>
 <li>
 Proven experience in data engineering, MLOps, ETL, and database management, QL and data manipulation languages.
 </li>
 <li>
 Azure, Python, Java, or Scala.
 </li>
 <li>
 data warehousing platforms (e.g., Databricks, Amazon Redshift, Snowflake) and big data technologies (e.g., Hadoop, Spark).
 </li>
 <li>
 highly scalable Data stores, Data Lake, Data Warehouse, Lakehouse, and unstructured datasets
 </li>
 </ul>
</div>

Data Scientist

<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.
 
 
 Data Engineer, Product Analytics Responsibilities:
 
 
 <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
 
 
 </li>
 </ul>
 Minimum Qualifications:
 
 
 <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.)
 
 
 </li>
 </ul>
 Preferred Qualifications:
 
 
 <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
 
 
 </li>
 </ul>
 About Meta:
 
 
 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.
 
 
 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.
 
 
 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.
 
 
 $147,000/year to $208,000/year + bonus + equity + benefits
 
 
 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">DESCRIPTION</h2><div>
Amazon Quick Suite is an enterprise AI platform that transforms how organizations work with their data and knowledge. Combining generative AI-powered search, deep research capabilities, intelligent agents and automations, and comprehensive business intelligence, Quick Suite serves tens of thousands of users. Our platform processes thousands of queries monthly, helping teams make faster, data-driven decisions while maintaining enterprise-grade security and governance. From natural language interactions with complex datasets to automated workflows and custom AI agents, Quick Suite is redefining workplace productivity at unprecedented scale. 
 
We are seeking a Data Scientist II to join our Quick Data team, focusing on evaluation and benchmarking data development for Quick Suite features, with particular emphasis on Research and other generative AI capabilities. Our mission is to engineer high-quality datasets that are essential to the success of Amazon Quick Suite. From human evaluations and Responsible AI safeguards to Retrieval-Augmented Generation and beyond, our work ensures that Generative AI is enterprise-ready, safe, and effective for users at scale. 
As part of our diverse team&mdash;including data scientists, engineers, language engineers, linguists, and program managers&mdash;you will collaborate closely with science, engineering, and product teams. We are driven by customer obsession and a commitment to excellence.
 
 
Key job responsibilities 
In this role, you will leverage data-centric AI principles to assess the impact of data on model performance and the broader machine learning pipeline. You will apply Generative AI techniques to evaluate how well our data represents human language and conduct experiments to measure downstream interactions. 
Specific responsibilities include: 
<ul><li>Design and develop comprehensive evaluation and benchmarking datasets for Quick Suite AI-powered features</li><li>Leverage LLMs for synthetic data corpora generation; data evaluation and quality assessment using LLM-as-a-judge settings</li><li>Create ground truth datasets with high-quality question-answer pairs across diverse domains and use cases</li><li>Lead human annotation initiatives and model evaluation audits to ensure data quality and relevance</li><li>Develop and refine annotation guidelines and quality frameworks for evaluation tasks</li><li>Conduct statistical analysis to measure model performance, identify failure patterns, and guide improvement strategies</li><li>Collaborate with ML scientists and engineers to translate evaluation insights into actionable product improvements</li><li>Build scalable data pipelines and tools to support continuous evaluation and benchmarking efforts</li><li>Contribute to Responsible AI initiatives by developing safety and fairness evaluation datasets</li></ul> 
About the team 
 
Why AWS? 
Amazon Web Services (AWS) is the world&rsquo;s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating &mdash; that&rsquo;s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. 
 
Inclusive Team Culture 
Here at AWS, it&rsquo;s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon conferences, inspire us to never stop embracing our uniqueness. 
 
Mentorship &amp; Career Growth 
We&rsquo;re continuously raising our performance bar as we strive to become Earth&rsquo;s Best Employer. That&rsquo;s why you&rsquo;ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. 
 
Work/Life Balance 
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there&rsquo;s nothing we can&rsquo;t achieve in the cloud. 
 
Hybrid Work 
We value innovation and recognize this sometimes requires uninterrupted time to focus on a build. We also value in-person collaboration and time spent face-to-face. Our team affords employees options to work in the office every day or in a flexible, hybrid work model near one of our U.S. Amazon offices.</div><h2 class="jobSectionHeader">
BASIC QUALIFICATIONS</h2><ul><li>2+ years of data scientist experience</li><li>3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience</li><li>3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience</li><li>1+ years of working with or evaluating AI systems experience</li><li>1+ years of creating or contributing to mathematical textbooks, research papers, or educational content experience</li><li>Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)</li><li>Experience applying theoretical models in an applied environment</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>Ph.D. in Science, Technology, Engineering, or Mathematics (STEM)</li><li>Knowledge of machine learning concepts and their application to reasoning and problem-solving</li><li>Experience in a ML or data scientist role with a large technology company</li><li>Experience in defining and creating benchmarks for assessing GenAI model performance</li><li>Experience working on multi-team, cross-disciplinary projects</li><li>Experience applying quantitative analysis to solve business problems and making data-driven business decisions</li><li>Experience effectively communicating complex concepts through written and verbal communication</li></ul> 
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. 
 
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company&rsquo;s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. 
 
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner. 
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life &amp; AD&amp;D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits. 
USA, CA, Santa Clara - 157,300.00 - 212,800.00 USD annually 
USA, NY, New York - 153,400.00 - 207,500.00 USD annually 
USA, WA, Seattle - 136,000.00 - 184,000.00 USD annually</div>

Data Scientist, AWS Quick Data

Amazon.com

<div><h2 class="jobSectionHeader">DESCRIPTION</h2><div>
If you are excited about applying your science and engineering skills in business problems in the space of Credit management, B2B Financial Service, and Payments, we invite you to consider this Applied Scientist opportunity within Amazon B2B Payments and Lending (ABPL). 
 
ABPL is seeking a Senior Applied Scientist who combines their scientific and technical expertise with business intuition to build flexible, performant, and global solutions for complex financial and risk problems. You will develop and deploy production models to enhance our product features &amp; processes that will delight our customers. 
 
Key job responsibilities 
As a Sr. Applied Scientist, you will design and build systems that support financial products. You will work closely with business partners, software and data engineers to build and deploy scalable solutions that deliver exceptional value for our customers. You will utilize intellectual and technical capabilities, problem solving and analytical skills, and excellent communication to deliver customer value. You will partner with product and operations management to launch new, or improve existing, financial products within Amazon. 
 
Responsibilities include: 
<ul><li>Understand business and product strategies, goals and objectives. Make recommendations for new techniques/strategies including GenAI innovations, agentic AI frameworks, and foundation models, and to improve customer experience and business outcomes</li><li>Apply advanced data mining, machine learning, and Generative AI techniques to create AI/ML capabilities and support Credit and Fraud Management
</li><li>Source, incorporate, and analyze alternative data to drive innovation, utilizing GenAI and foundation models
</li><li>Own production models (real time and batch), conduct code review and model monitoring to insist high bar of operating excellence and ensure high performant models
</li><li>Conduct research and educate business, product, marketing and product teams on the implementation of models and GenAI innovations, enabling strategic decision making through AI-powered insights and automation 
</li></ul> 
 
 
A day in the life 
Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: 1. Medical, Dental, and Vision Coverage 2. Maternity and Parental Leave Options 3. Paid Time Off (PTO) 4. 401(k) Plan. 
 
If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you&rsquo;re passionate about this role and want to make an impact on a global scale, please apply!</div><h2 class="jobSectionHeader"> 
BASIC QUALIFICATIONS</h2><ul><li>Master's degree or equivalent in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science</li><li>5+ years experience in a science role, applying AI/ML to solve complex problems for large-scale applications</li><li>Demonstrated fluency with GenAI tools (e.g., LLMs, code assistants) to accelerate model development, feature engineering, and code generation workflows</li><li>Superior analytical skills. Demonstrated ability to identify and solve ambiguous problems</li><li>Demonstrated attention to detail and desire to roll up your sleeves</li><li>Demonstrated ability to operate both strategically and tactically in a high-energy, fast-paced environment. High degree of organization and ability to manage multiple, competing priorities</li><li>Excellent communication (verbal and written) and collaboration skills that enable you to earn trust at all levels</li><li>Proficiency in Python, SQL, or other programming language</li><li>Experience developing machine learning solutions with AWS</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>Ph.D. in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science</li><li>10+ years of practical work applying AI/ML to solve complex problems for large-scale applications experience</li><li>Experience designing and deploying AI-native systems that leverage foundation models, agentic frameworks, and LLM-powered automation</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><li>3+ years experience in credit underwriting or related work in financial services domain</li><li>Project management experience for working on cross-functional projects</li><li>Proven achievements of developing and managing a long-term research vision and portfolio of research initiatives, with algorithms and models that have been successfully integrated in production systems</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 - 183,800.00 - 248,700.00 USD annually 
USA, WA, Seattle - 167,100.00 - 226,100.00 USD annually</div>

Sr. Applied Scientist, Amazon B2B Payments and Lending, Credit and Fraud Science

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