We are seeking a passionate Data Scientist with deep expertise in optimization and causal inference to join our team. You will work on some of the most challenging problems in DSP delivery planning and the business health space, applying data science rigor to improve how decisions are made and drive outcomes at scale.

Key job responsibilities

Develop Science Solutions for DSP Capacity Planning & Business Health: Design and implement data science solutions that optimize Delivery Service Partner (DSP) capacity allocation and business health measurement across the global DSP network. Leverage deep expertise in mathematical optimization and causal inference to identify opportunities for improving capacity planning models, volume share calibration methodologies, and business health measurement systems that drive partner sustainability.

Analyze Sentiment Risks & Business Health Metrics: Analyze sentiment risks and enhance algorithms that support DSP program management, including business health indicators, capacity reliability models, and partner viability frameworks that inform intervention strategies.

Translate Business Requirements into Mathematical Models: Demonstrate strategic thinking by translating high-level DSP capacity planning and business health improvement requirements into optimization formulations and predictive models, and applying them to quantify return on investment for policy changes and network interventions.

Build Production-Scale Analytics: Contribute to the development and deployment of scalable data models, dashboards, and automated reporting systems that enable self-service analytics for DSP stakeholders and surface business health signals at scale.

Accelerate GenAI Footprint: Partner with Data Engineers to expand our GenAI tools and improve developer productivity, while raising the bar on data quality and enabling intelligent automation across capacity planning workflows.

Conduct Independent Data Analysis: Mine and analyze complex datasets across multiple domains, business health metrics, financial data, capacity signals, and operational data, using programming and statistical tools to generate actionable insights.

Thrive in a Collaborative Environment: Excel in a fast-paced analytics organization that encourages collaborative and creative problem-solving. Measure and communicate analytical risks, constructively critique peer work, and align research focuses with DSP capacity planning strategic needs.

Partner Cross-Functionally: Work closely with Business Intelligence Engineers, capacity planning teams, and DSP stakeholders to define KPIs, validate analytical approaches, and ensure insights drive meaningful outcomes.

BASIC QUALIFICATIONS

- Master's degree in econometrics, statistics, industrial engineering, operations research, optimization, data mining, analytics, or equivalent quantitative field, or experience working in Science, Technology, Engineering, or Mathematics (STEM)

- 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

- 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience

- 2+ years of data scientist experience

- 2+ years of a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science experience

- 1+ years of working with or evaluating AI systems experience

- Experience applying quantitative analysis to solve business problems and making data-driven business decisions

- Experience effectively communicating complex concepts through written and verbal communication

PREFERRED QUALIFICATIONS

- Ph.D. in econometrics, statistics, industrial engineering, operations research, optimization, data mining, analytics, or equivalent quantitative field

- Experience in a ML or data scientist role with a large technology company

- Knowledge of machine learning concepts and their application to reasoning and problem-solving

- Experience implementing algorithms using both toolkits and self-developed code

- Experience in defining and creating benchmarks for assessing GenAI model performance

- Experience working on multi-team, cross-disciplinary projects

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 & AD&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, Bellevue - 136,000.00 - 184,000.00 USD annually