Full Job Description
As a Data Science Manager (DSM), you will lead a team of economists, scientists, and data engineers working to solve complex scientific problems that have high business and customer impact. You will be responsible for building structural and predictive models, leveraging data science workflows, and driving innovations that deliver measurable results for Amazon customers.
You will work shoulder-to-shoulder with economists who deeply understand the causal mechanisms driving workforce dynamics and data scientists who know the operational landscape - and you will bring the technical creativity to expand what's possible. That means writing production-quality code that our partner engineering teams can implement into decision-making tools. It means exploring novel feature spaces - large language models, computer vision, and other emerging techniques - to unlock signal that traditional approaches miss. And it means doing all of this with the scientific rigor that causal claims demand.
This role is built for someone who is entrepreneurial and energized by ambiguity - someone who sees a prototype model and immediately starts thinking about how to make it robust, scalable, and impactful. You will not just advance your own work; you will elevate the scientists around you.
If you want to do science that directly shapes how Amazon supports its workforce - not in theory, but in production systems that leaders use to make better decisions every day - we'd love to talk.
Key job responsibilities
- Leadership & Team Management: Independently manage and develop a diverse science team, creating an environment that enables consistent delivery and innovation; Build and maintain a high-performing team that can operate effectively and autonomously; Drive strategic growth opportunities for team members, providing paths to demonstrate higher-level scope, impact, and leadership; Establish clear performance metrics and audit mechanisms to track and communicate team progress; Foster a team culture focused on bringing research to production and delivering customer value
- Technical & Scientific Direction: Partner with stakeholders and leadership to define and execute the scientific vision for your team; Lead the development of structural and predictive models, leveraging emerging technologies and novel features; Drive the implementation of data science workflows and simulation frameworks; Bridge the gap between science, technology, and business requirements; Leverage the broader Amazon scientific community to enhance team capabilities and knowledge sharing
- Strategic Planning & Execution: Define and maintain team structure, strategic direction, and owned technologies; Establish processes that enable consistent delivery and quality of scientific artifacts; Drive reasonable schedules and adjust priorities to ensure optimal outcomes; Create and implement audit mechanisms to track team performance against goals; Remove roadblocks and optimize team productivity
- Communication & Influence: Create well-written documents to effectively communicate with technical and non-technical audiences; Influence science and analytics practices across the organization; Build strong partnerships with stakeholders across different business units; Present complex scientific findings to senior leadership; Drive adoption of best practices and innovative solutions
About the team
The Central Science Team within Amazon's People Experience and Technology org (PXTCS) uses economics, behavioral science, statistics, machine learning, and Generative AI to proactively identify mechanisms and process improvements which simultaneously improve Amazon and the lives, well-being, and the value of work to Amazonians. We are an interdisciplinary team, which combines the talents of science and UX to develop and deliver solutions that measurably achieve this goal.
BASIC QUALIFICATIONS
- 5+ years of building quantitative solutions as a scientist or science manager experience
- 2+ years of scientists or machine learning engineers management experience
- 5+ years of applying statistical models for large-scale application and building automated analytical systems experience
- Master's degree in computer science, mathematics, statistics, machine learning or equivalent quantitative field
- Knowledge of Python or R or other scripting language
PREFERRED QUALIFICATIONS
- Experience in a least one area of Machine Learning (NLP, Regression, Classification, Clustering, or Anomaly Detection)
- Experience with fairness in machine learning and artificial intelligence to detect and remove bias in ML/AI systems
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, CA, San Francisco - 201,300.00 - 272,400.00 USD annually
USA, MA, Boston - 175,100.00 - 236,900.00 USD annually
USA, VA, Arlington - 175,100.00 - 236,900.00 USD annually
USA, WA, Bellevue - 175,100.00 - 236,900.00 USD annually
USA, WA, Seattle - 175,100.00 - 236,900.00 USD annually
