lead data scientist- pricing, data & analytics (seattle, wa)

performance and data analytics specialist

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lead data scientist- pricing, data & analytics (seattle, wa) Jobs in Seattle

performance and data analytics specialist Jobs in Seattle

data scientist

Starbucks

<div>Now Brewing &ndash; Lead Data Scientist! #tobeapartner 
 
From the beginning, Starbucks set out to be a different kind of company. One that not only celebrated coffee and the rich tradition, but that also brought a feeling of connection. We are known for developing extraordinary leaders who share this passion and are guided by their service to others.
As a Lead Data Scientist on the Pricing Data Science team, you will lead the development of advanced pricing models and optimization algorithms that shape pricing decisions across US and Canada company-owned stores. You will drive the evolution of the pricing system by applying rigorous analytics, partnering with cross-functional teams, and influencing strategic workforce planning. Your work will directly impact pricing, and customer experience at scale.
As a lead data scientist, you will&hellip; 
Design and Architect the Future Pricing Ecosystem<ul><li>
Build a scalable, data-driven pricing framework that optimizes revenue.</li><li>
Incorporate predictive modeling, and ad hoc analyses into pricing framework. 
Drive Pricing and Revenue management data science</li><li>
Identify pricing and promotion potential through advanced analytics.</li><li>
Implement optimization strategies leveraging machine learning, simulation, and scenario planning.</li><li>
Partner with strategy and finance to align pricing tools with business goals. 
Mentor and Develop Talent</li><li>
Guide data scientists and senior data scientists in advanced analytics, optimization techniques, and business impact storytelling.</li><li>
Foster a culture of innovation and continuous improvement within the analytics team.</li></ul> 


We&rsquo;d love to hear from people with:<ul><li>
5+ years of progressive experience in data science, with a proven track record of end-to-end data product and model deployment that delivers measurable business impact.</li><li>
Strong foundation in machine learning and statistical techniques, including regression, classification, clustering, and causal inference.</li><li>
Advanced proficiency in Python, SQL, and cloud-based analytics platforms (e.g., Databricks, Azure), with experience developing production-grade data pipelines and model outputs.</li><li>
Excellent communication and data storytelling skills, with the ability to translate complex methodologies into clear, actionable insights through compelling visualizations and dashboards using tools like Tableau.</li><li>
Experience building in-house production systems in complex and data-rich domains.</li><li>
Mentoring experience</li></ul> 
Preferred Skills:<ul><li>
Expertise in building Bayesian elasticity models and causal inference</li><li>
Experience in optimization techniques such as linear programming, mixed-integer programming, or heuristic algorithms for decision support</li><li>
Background with PySpark and Databricks for distributed data processing and scalable analytics in cloud environments</li></ul><div> 
As a Starbucks partner, you (and your family) will have access to medical, dental, vision, basic and supplemental life insurance, and other voluntary insurance benefits. Partners have access to short-term and long-term disability, paid parental leave, family expansion reimbursement, paid vacation from date of hire*, sick time (accrued at 1 hour for every 25 hours worked), eight paid holidays, and two personal days per year. Starbucks also offers eligible partners participation in a 401(k) retirement plan with employer match, a discounted company stock program (S.I.P.), Starbucks equity program (Bean Stock), incentivized emergency savings, and financial well-being tools. Additionally, Starbucks offers 100% upfront tuition coverage for a first-time bachelor&rsquo;s degree through Arizona State University&rsquo;s online program via the Starbucks College Achievement Plan, student loan management resources, and access to other educational opportunities. You will also have access to backup care and DACA reimbursement. Starbucks will comply with any applicable state and local laws regarding employee leave benefits, including, but not limited to providing time off pursuant to the Colorado Healthy Families and Workplaces Act, and in accordance with its plans and policies. This list is subject to change depending on collective bargaining in locations where partners have a certified bargaining representative. For additional information regarding partner perks and more detailed information about benefits, go to starbucksbenefits.com. 
<ul><li>If you are working in CA, CO, IL, LA, ME, MA, NE, ND or RI, you will accrue vacation up to a maximum of 120 hours (190 in CA) for roles below director and 200 hours (316 in CA) for roles at director or above. For roles in other states, you will be granted vacation time starting at 120 hours annually for roles below director and 200 hours annually for roles director and above.</li></ul></div>
The actual base pay offered to the successful candidate will be based on multiple factors, including but not limited to job-related knowledge/skills, experience, geographical location, and internal equity. At Starbucks, it is not typical for an individual to be hired at the high end of the range for their role, and compensation decisions are dependent upon the facts and circumstances of each position and candidate.
We believe we do our best work when we're together, which is why we're onsite four days a week. 
Join us and inspire with every cup. Apply today! 
Starbucks Coffee Company is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, age, national origin, disability, or protected veteran status, or any other characteristic protected by law. 
Qualified applicants with criminal histories will be considered for employment in a manner consistent with all federal, state and local ordinances. 
 
Starbucks Coffee Company is committed to offering reasonable accommodations to job applicants with disabilities. If you need assistance or an accommodation due to a disability, please contact us at applicantaccommodation@starbucks.com or 1(888) 611-2258.</div>

lead data scientist- Pricing, Data & Analytics (Seattle, WA)

Amazon Web Services

<div><h2 class="jobSectionHeader">DESCRIPTION</h2>
At AWS Cloud &amp; AI Innovation team, our mission is to accelerate customer adoption of AI and maximize the value they get from this technology.
 
 
As Applied Scientist on our team, your focus will be on solving the most complex problems that prevent our customers from successfully adoption AI at scale. You will research new methods for overcoming obstacles that are beyond engineering solutions. These include advanced methods for agent grounding and evals, novel methods for multi-agent orchestration and semantic data layer, and innovative approaches to optimizing customer token costs, just to name a few.
 
 
A successful candidate will have a strong machine learning background, a deep understanding of the AI stack, and a desire to push the envelope in applying AI to the most difficult practical problems preventing adoption at scale and in business-critical situations. 
 
As a senior member of the team, you will own ambiguous, high-impact research problems end-to-end &mdash; from defining the scientific direction to conducting the research, to packaging it into a reusable solution that the rest of the team can apply in customer-facing engagements.
 
 
As an Applied Scientist, you will leverage your technical expertise to set the research agenda for how we measure conversational quality, mentor engineers and architects, and partner across science, engineering, and business teams. You will analyze and understand customer experiences and develop novel approaches to solving complex problems in applied AI.<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. 
 
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner. 
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life &amp; AD&amp;D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits. 
USA, WA, Seattle - 167,100.00 - 226,100.00 USD annually</div>

Sr. Applied Scientist, CAIT

Amazon.com

<div><h2 class="jobSectionHeader">DESCRIPTION</h2><div>
Here's the job description with causal ML woven in: 
 
We are looking for a talented, organized, and customer-focused applied researcher to join our Pricing Optimization science group, with a charter to measure, refine, and launch customer-obsessed improvements to our algorithmic pricing and promotion models across all products listed on Amazon. 
 
This role requires an individual with exceptional machine learning modeling and architecture expertise &mdash; particularly in deep learning, neural networks, and transformer-based architectures applied to price prediction and forecasting problems. Equally important is deep expertise in causal machine learning &mdash; including causal inference, treatment-effect estimation, and experimentation methods (e.g., uplift modeling, double/debiased machine learning, instrumental variables, and A/B and quasi-experimental design) &mdash; to isolate the true impact of pricing and promotion decisions on customer behavior and business outcomes. The ideal candidate brings a strong foundation in applied statistics and probabilistic modeling, excellent cross-functional collaboration skills, business acumen, and an entrepreneurial spirit. 
 
We are looking for an experienced innovator who is a self-starter, comfortable with ambiguity, demonstrates strong attention to detail, and has the ability to work in a fast-paced and ever-changing environment. 
 
Key job responsibilities 
See the big picture. Understand and influence the long-term vision for Amazon's science-based competitive, perception-preserving pricing techniques. Develop and advance price prediction models leveraging deep learning frameworks, transformer architectures, and advanced statistical methods to drive pricing accuracy at scale. 
 
Build strong collaborations. Partner with product, engineering, and science teams within Pricing &amp; Promotions to deploy machine learning price estimation and error correction solutions at Amazon scale. Design and implement neural network-based architectures &mdash; including sequence models and transformers &mdash; for large-scale price prediction and optimization. 
 
Stay informed. Establish mechanisms to stay up to date on the latest scientific advancements in deep learning, transformer architectures, applied statistics, neural network design, probabilistic forecasting, and multi-objective optimization techniques. Identify opportunities to apply them to relevant Pricing &amp; Promotions business problems. 
 
Keep innovating for our customers. Foster an environment that promotes rapid experimentation, continuous learning, and incremental value delivery. Leverage statistical rigor and modern deep learning approaches to validate hypotheses and drive measurable pricing improvements. 
 
Successfully execute &amp; deliver. Apply your exceptional technical machine learning expertise &mdash; including deep neural networks, attention-based models, and applied statistical analysis &mdash; to incrementally move the needle on some of our hardest pricing problems. 
 
A day in the life 
We are hiring a Sr. Applied Scientist to drive our pricing optimization initiatives. We drive cross-domain and cross-system improvements through: 
 
<ul><li>shape and extend our RL optimization platform - a pricing centric tool that automates the optimization of various system parameters and price inputs.</li><li>Error detection and price quality guardrails at scale.</li><li>Identifying opportunities to optimally price across systems and contexts (marketplaces, request types, event periods)</li></ul> 
Price is a highly relevant input into Stores architectures; this role creates the opportunity to drive extremely large impact (measured in Bs not Ms), but demands careful thought and clear communication. 
 
About the team 
The Pricing Optimization science group builds and refines Amazon's algorithmic pricing and promotion models at scale. Our team combines expertise in deep learning, transformer architectures, applied statistics, and probabilistic forecasting to develop price prediction systems that directly impact the customer experience. The team also brings hands-on experience with causal modeling and inference &mdash; including uplift modeling and treatment effect estimation &mdash; to rigorously measure the impact of pricing decisions on customer behavior and business outcomes. We partner closely with product, engineering, and business teams to take solutions from research through production deployment.</div><h2 class="jobSectionHeader"> 
BASIC QUALIFICATIONS</h2><ul><li>4+ years of applied research experience</li><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. 
 
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner. 
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life &amp; AD&amp;D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits. 
USA, WA, Seattle - 167,100.00 - 226,100.00 USD annually</div>

Sr. Applied Scientist, Pricing Science

Whatnot

<div>
 
 
 🚀 Join the Future of Commerce with Whatnot!
 
 
 
 
 Whatnot is the largest live shopping platform in North America and Europe to buy, sell, and discover the things you love. Whether it's trading cards, fashion, electronics, or live plants, our sellers are building real businesses across hundreds of categories. We're building live commerce at a scale that's never been done in the West, and there's no playbook to copy. The people here are shaping how an entirely new industry develops.
 
 
 As a remote co-located team, we're inspired by our values and anchored in hubs across the US, UK, Ireland, Poland, Germany, and Australia. We move fast, stay close to our users, and focus on the work that drives the most impact.
 
 
 We're one of the fastest growing marketplaces and were recently named the #1 Best Startup Employer in America by Forbes. Check out the latest Whatnot updates on our news and engineering blogs and join us as we enable anyone to turn their passion into a business and bring people together through commerce.
 
 
 
 💻 Role
 
 
 
 Data is crucial to Whatnot&rsquo;s mission to bring people together through commerce.
 
 
 As our newest
 
 Data Engineer
 
 , you&rsquo;ll build and scale the systems that power data-driven decisions across the company. You&rsquo;ll work directly with stakeholders across the business &ndash; such as product, sales, marketing, finance, and trust teams &ndash; to design reliable data architectures, ship resilient pipelines, and create the foundational data products that power Whatnot&rsquo;s internal and external growth.
 
 
 
 On Any Given Day, You Will
 
 
 
 <ul>
 <li>
 Own data architecture end-to-end. Define how we capture, model, and serve critical business data&mdash;then implement it in production. You&rsquo;ll make architectural decisions around storage formats, compute patterns, and SLAs that balance cost, scalability, and consistency.
 </li>
 <li>
 Build mission-critical pipelines. Develop and operate streaming and batch data workflows that process high-volume events across multiple domains&mdash;user activity, transactions, experimentation, marketing performance, and operational telemetry&mdash;with tight guarantees for latency, completeness, and accuracy.
 </li>
 <li>
 Design and implement canonical models. Create domain-oriented data models that serve as the source of truth for analytics, ML, and real-time applications. Establish and enforce modeling standards, ownership boundaries, and data contracts across teams.
 </li>
 <li>
 Enforce data quality at scale. Build tests, lineage, monitoring, and reconciliation systems that make every dataset observable and every anomaly actionable.
 </li>
 <li>
 Automate operational workflows. Partner with business systems and platform teams to eliminate manual data handoffs and reconcile data across services, warehouses, and external systems.
 </li>
 <li>
 Enable insights and experimentation. Support analytics, ML, and product engineering teams by exposing high-quality, low-latency data through semantic layers, APIs, and real-time query systems.
 
 
 </li>
 </ul>
 Due to the cross-functional nature of this role, candidates will be matched to multiple teams based on need and experience, including product, analytics, or data platforms teams.
 
 
 
 👋 You
 
 
 
 People who do well at Whatnot tend to be comfortable figuring things out as they go, biased toward action, and genuinely curious about what they're building. They care more about outcomes than credit and stay close to the product and the people using it.
 
 
 <ul>
 <li>
 Have 3+ years of experience as a data or software engineer building data warehouses, distributed data systems, or event-driven architectures.
 </li>
 <li>
 Can design and implement data models using dimensional, Data Vault, or ledger-style techniques that support analytical and transactional workloads.
 </li>
 <li>
 Have deep hands-on expertise with modern data tooling across ingestion (e.g., Kafka, Debezium), transformation (dbt, Spark, Flink), orchestration (Dagster, Airflow), and observability (Monte Carlo, Great Expectations).
 </li>
 <li>
 Have operated cloud data warehouses such as Snowflake, BigQuery, or Redshift, including schema design, cost optimization, and workload tuning.
 </li>
 <li>
 Are comfortable writing production-grade code in Python or SQL languages, and integrating with CI/CD and infrastructure-as-code workflows.
 </li>
 <li>
 Enjoy partnering across disciplines&mdash;engineering, product, analytics&mdash;to translate messy business requirements into elegant data systems.
 </li>
 <li>
 Thrive as a self-starter in a fast-moving environment, owning both the technical design and the operational outcomes of your work.
 
 
 </li>
 </ul>
 If designing the data backbone that powers Whatnot&rsquo;s growth, insights, and product innovation excites you, we&rsquo;d love to meet you.
 
 
 
 We offer flexibility to work from home or from one of our global office hubs, and we value in-person time for planning, problem-solving, and connection. Team members in this role must live within commuting distance of our New York, Seattle, Los Angeles, and San Francisco hubs.
 
 
 
 
 💰Compensation
 
 
 
 
 For Full-Time (Salary)
 
 
 
 
 US based applicants:
 
 $180,000/year to $260,000/year + benefits + equity.
 
 
 The salary range may be inclusive of several levels that would be applicable to the position. Final salary will be based on a number of factors including, level, relevant prior experience, skills, and expertise. This range is only inclusive of base salary, not benefits (more details below) or equity.
 
 
 
 🎁 Benefits
 
 
 
 <ul>
 <li>
 Generous Holiday and Time off Policy
 </li>
 <li>
 Health Insurance options including Medical, Dental, Vision
 </li>
 <li>
 Work From Home Support
 </li>
 <ul>
 <li>
 Home office setup allowance
 </li>
 <li>
 Monthly allowance for cell phone and internet
 </li>
 </ul>
 <li>
 Care benefits
 </li>
 <ul>
 <li>
 Monthly allowance for wellness
 </li>
 <li>
 Annual allowance towards Childcare
 </li>
 <li>
 Lifetime benefit for family planning, such as adoption or fertility expenses
 </li>
 </ul>
 <li>
 Retirement; 401k offering for Traditional and Roth accounts in the US (employer match up to 4% of base salary) and Pension plans internationally
 </li>
 <li>
 Monthly allowance to dogfood the app
 </li>
 <ul>
 <li>
 All Whatnauts are expected to develop a deep understanding of our product. We're passionate about building the best user experience, and all employees are expected to use Whatnot as both a buyer and a seller as part of their job (our dogfooding budget makes this fun and easy!).
 </li>
 </ul>
 <li>
 Parental Leave
 </li>
 <ul>
 <li>
 16 weeks of paid parental leave + one month gradual return to work *company leave allowances run concurrently with country leave requirements which take precedence.
 </li>
 </ul>
 </ul>
 
 
 💛 EOE
 
 
 
 
 Whatnot is proud to be an Equal Opportunity Employer. We value diversity, and we do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, parental status, disability status, or any other status protected by local law. We believe that our work is better and our company culture is improved when we encourage, support, and respect the different skills and experiences represented within our workforce.
 
 
 Compensation Range: $180K - $260K
 
 
</div>

Data Engineer

<div><h2 class="jobSectionHeader">DESCRIPTION</h2><div>
Are you passionate about building business insights that drive decision-making at the highest levels? Do you want to be part of a fast-paced, ambiguous environment and contribute to Amazon's Brand Protection charter? 
 
As a Sr. Business Intelligence Engineer, from Day 1, you will be challenged with solving complex and ambiguous data problems - from designing scalable data models and metric frameworks, to building executive-ready dashboards, owning pipeline architecture and driving the technical strategy for the data team. 
 
What are we looking for? 
<ul><li>You have a track record of end-to-end ownership and successfully delivering results in a fast-paced and dynamic business environment.</li><li>You are passionate about finding root causes, trends, and patterns and how they impact business. You use data to support your ideas and drive actionable outcomes, and draw inferences and conclusions based on data.</li><li>You should be able to work on complex initiatives, deal with ambiguity, and work with senior leaders.</li><li>You have extensive experience working with extremely large data sets and are comfortable with various tools and technologies to consume, extract, and transform data.</li><li>You have business communication skills to be able to work with product and program owners to understand key business questions, and are able to build solutions (analysis / reports / dashboards) that enable them to answer those questions quickly and accurately.</li><li>You are comfortable juggling competing priorities and handling ambiguity. You thrive in an agile and fast-paced environment on highly visible projects and initiatives.</li></ul>
- You have experience mentoring engineers and raising the technical bar for a team - through code reviews, architectural guidance, and leading by example. 
 
Key job responsibilities 
<ul><li>Be highly data driven, resourceful, and team oriented.</li><li>Translate analytic insights into actionable recommendations for business and clearly communicate strategic findings by translating complex technical concepts into business terms and vice versa.</li><li>Develop dashboards that provide insights into the health of the business, create analytics solutions to drive deep dives and uncover hidden risks/trends and recommend optimizations for future state.</li><li>Interact with internal program, product, engineering, data and science owners to gather requirements, structure scalable and performant data solutions and gain a deep understanding of key datasets.</li><li>Own the design, creation, and management of extremely large datasets and tune query performance against large and complex data sets.</li><li>Design, implement, and drive adoption of new analytic technologies and solutions and promote industry standard best practices.</li></ul>
- Serve as the technical lead for the Brand Protection data team - owning architectural decisions, mentoring engineers and analysts on best practices, query optimization, and data modeling. 
 
About the team 
 
The Brand Protection team is part of Amazon's WW Customer &amp; Partner Trust organization. Our vision is to use data provided by Brands in the Brand Registry to prevent Brands eligible for protections worldwide from ever seeing a listing on Amazon that has invalid data (e.g., misuse of trademarks, copyright) associated with their Brand. We strive to make Amazon the best way for Selling Partners to operate their businesses by protecting their intellectual property while reaching customers locally and globally.</div><h2 class="jobSectionHeader">
BASIC QUALIFICATIONS</h2><ul><li>10+ years of professional or military experience</li><li>5+ years of SQL experience</li><li>Experience programming to extract, transform and clean large (multi-TB) data sets</li><li>Experience with theory and practice of design of experiments and statistical analysis of results</li><li>Experience with AWS technologies</li><li>Experience in scripting for automation (e.g. Python) and advanced SQL skills.</li><li>Experience with theory and practice of information retrieval, data science, machine learning and data mining</li><li>Knowledge of data warehousing and data modeling</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>Experience working directly with business stakeholders to translate between data and business needs</li><li>Experience managing, analyzing and communicating results to senior leadership</li><li>Experience with data visualization using Tableau, Quicksight, or similar tools</li></ul> 
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. 
 
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner. 
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life &amp; AD&amp;D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits. 
USA, WA, Seattle - 130,400.00 - 176,300.00 USD annually</div>

Business Intelligence Engineer III, Intellectual Property Protection

<div><h2 class="jobSectionHeader">DESCRIPTION</h2><div>
Do you want to join an innovative team of scientists and engineers who use terabytes of data and create state-of-the-art Generative AI algorithms to push the boundaries of AI creativity? We are building foundational behavioral models for Amazon Stores using Generative AI, LLMs and Large Model training techniques that fuses general world knowledge, customer shopping behavior and Amazon e-commerce domain knowledge. We are looking for scientists who are passionate about technology, innovation, and customer experience, and are ready to make a lasting impact on the industry using intelligent and transformative AI applications. Working closely with cross-functional teams, you will be an essential part of every stage of AI development, from ideation and design to rigorous testing and successful deployment, ensuring our AI projects drive innovation and provide value for our customers. If you&rsquo;re fired up about being part of a dynamic, driven team, then this is your moment to join us on this exciting journey! 
 
Key job responsibilities 
In this role you will leverage your background and expertise to lead developing foundational behavioral model for Amazon Stores using Generative AI, LLM and Large Model training techniques. On a day-to-day basis, you will: 
<ul><li>Research and implement new algorithms and architectures for generative AI applications.</li><li>Optimize model performance and scalability for inference and deployment.</li><li>Collaborate with other talented applied scientists and engineers to gather and preprocess large datasets and develop an improved training infrastructure that accelerates innovation.</li><li>Experiment with SOTA methods to improve generative AI model quality.</li><li>Provide technical expertise and guidance to support the integration of generative AI solutions into various products and services.</li></ul></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>2+ years of building models for business application experience</li><li>Experience programming in Java, C++, Python or related language</li><li>Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing</li><li>Experience in patents or publications at top-tier peer-reviewed conferences or journals</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>Strong understanding of machine learning, deep learning, and generative AI principles and algorithms.</li><li>Proficiency with modeling and large-scale data processing tools such as Pytorch, scikit-learn, Spark MLLib, PySpark, MxNet, Tensorflow, numpy, scipy etc.</li><li>Ability to work with large datasets and knowledge of data preprocessing techniques such as Hadoop, Spark etc..</li><li>Familiarity with natural language processing (NLP) and computer vision for generative AI applications.</li><li>Strong problem-solving and critical thinking skills and excellent communication and teamwork abilities to collaborate with cross-functional teams.</li><li>Ability to stay updated with the latest advancements in generative AI and adapt to new techniques and methodologies.</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, San Diego - 142,800.00 - 193,200.00 USD annually 
USA, WA, Seattle - 142,800.00 - 193,200.00 USD annually</div>

Applied Scientist (GenAI/LLM), Sandstone

<div><h2 class="jobSectionHeader">DESCRIPTION</h2><div>
Amazon's mission is to be Earth's most customer-centric company, and our Amazon Customer Service (CS) organization is an essential part of that mission. CS is one of the largest customer service organizations in the world with hundreds of thousands of associates providing support 24/7 in over 22 languages. 
 
The Network Solutions org within CS is building intelligent, adaptive systems that match customers to optimal experiences and continuously improve service quality at scale. The Journey Management (JM) Team within Network Solutions is looking for a Senior Business Intelligence Engineer to own the data modeling, analytics, and metrics infrastructure for Precision Match, the foundational capability that routes customers to the right support the first time for complete resolution. Journey Completion is the learning and corrective arm of Journey Management building Match Quality Intelligence that runs the flywheel to continuously refine matching quality and develops associates. 
 
In this role, you will design analytics-ready data models that transform raw pipeline data into structured datasets enabling inspection of matching quality at scale. You will own executive-facing dashboards and automated reporting for P0 Precision Match metrics including First Contact Resolution Rate, Transfer Rate, repeat contact rates, and attribution breakdowns. You will build BI capabilities that enable cross-functional partners to inspect matching performance and surface actionable insights without ad-hoc manual analysis. You will partner with engineering and science teams to define metrics governance, ensure data fidelity, and establish sources of truth for Precision Match reporting. 
The ideal candidate is a self-starter comfortable with ambiguity who communicates effectively across technical and non-technical teams and seeks to tell the story of the data with little direction. 
 
Key job responsibilities 
As the Senior Business Intelligence Engineer (BIE) for Journey Completion, you will be the single-threaded owner of the analytics and reporting infrastructure that powers Precision Match decision-making. You will operate at the intersection of data engineering, business intelligence, and product analytics, building systems that make matching performance visible, measurable, and actionable for leadership and cross-functional partners across a global CS network serving 500M+ annual contacts. 
 
Data Modeling and Dataset Engineering 
<ul><li>Design and build analytics-ready data models transforming raw pipeline data from matching, routing, and contact resolution systems into structured, queryable datasets.</li><li>Develop enriched datasets combining internal contact, associate, and routing data with attribution signals, applying data quality checks and ensuring source-to-consumption fidelity.</li><li>Work with cross-functional stakeholders to define and maintain sources of truth for Precision Match metrics. Obsessively monitor data fidelity and own resolution when issues arise.</li></ul> 
Executive Reporting and Dashboards 
<ul><li>Build and own executive-facing dashboards and automated reports (daily, weekly, monthly business reviews) for P0 Precision Match metrics and attribution breakdowns.</li><li>Create standardized reporting and operational templates driving consistent metrics tracking across Journey Management leadership.</li></ul> 
Analytics and Business Intelligence 
<ul><li>Develop analytics solutions enabling cross-functional partners to inspect matching performance, identify trends, and surface actionable insights at scale.</li><li>Manipulate and mine data from Redshift, MySQL, and other sources to perform root cause analyses on matching failures, answer complex business questions, and surface new insights on routing quality and associate performance.</li><li>Quantify Precision Match performance through attribution modeling distinguishing suboptimal matching from planning/supply factors and associate execution gaps.</li><li>Lead business discussions to share insights, challenge status quo, and provide forward-looking recommendations to enable strategic decision making and growth of Precision Match.</li></ul> 
AI-Enhanced Reporting 
<ul><li>Build AI-powered reporting solutions including LLM-assisted insights, automated narrative generation, and intelligent alerting extending what stakeholders can do independently with data.</li></ul> 
Cross-Functional Partnership 
<ul><li>Partner with engineering and science teams on metrics governance and data capture at source.</li><li>Translate complex business needs into clear data solutions across Journey Management, Precision Match science, and associate development teams.</li></ul> 
About the team 
You will be part of a Product and Technology team in Customer Service/ Network Solutions org building the intelligence to understand why a match results in a transfer or repeat contact, applying attribution logic that distinguishes suboptimal matching from planning/supply factors and associate execution gaps. You will work alongside SDEs, BIEs, Data Engineers, Scientists, TPMs, and Product Managers to build the closed-loop feedback system continuously optimizing matching and developing associates serving 500M+ annual contacts.</div><h2 class="jobSectionHeader">
BASIC QUALIFICATIONS</h2><ul><li>1+ years of SQL, ETL or Oracle experience</li><li>1+ years of developing automated reporting experience</li><li>5+ years of as a Data Analyst, Data Engineer, Business Intelligence Analyst, or a related occupation experience</li><li>Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, Statistics, Economics, or a related field</li><li>Experience with theory and practice of information retrieval, data science, machine learning and data mining</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>Experience working directly with business stakeholders to translate between data and business needs</li><li>Experience managing, analyzing and communicating results to senior leadership</li><li>Experience programming to extract, transform and clean large (multi-TB) data sets</li><li>Experience with AWS technologies</li><li>Experience with theory and practice of design of experiments and statistical analysis of results</li></ul> 
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. 
 
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner. 
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life &amp; AD&amp;D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits. 
USA, WA, Seattle - 130,400.00 - 176,300.00 USD annually</div>

Senior Business Intelligence Engineer, Amazon Customer Service

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