Applied Scientist, People eXperience Technology Central Science (PXTCS)

The Central Science Team within Amazon’s People Experience and Technology org (PXTCS) uses economics, behavioral science, statistics, and machine learning 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 engineering to develop and deliver solutions that measurably achieve this goal.

We are looking for an Applied Scientist to build models at the intersection of prediction, causal inference, and optimization. These models are the science foundation for operational workforce planning at Amazon's scale — predicting who stays, who shows up, and suggesting which levers Amazon should use to ensure smooth business operations and the best employee experience.

As an Applied Scientist, you will own the forecasting and prediction models. Your forecasts go straight into planning cycles that commit real hiring, so accuracy, calibration, and being able to explain a number to business partners all matter for success. You will work with other scientists and economists on the team, so you will need an interdisciplinary mindset and an eye on how causal inference and forecasting interact. You will also collaborate with engineers to put models into production, so you should be comfortable owning a live system and not only an analysis.


Key job responsibilities
- Design and develop forecasting and prediction models that feed Amazon's workforce planning and optimization systems.
- Build models and algorithms from prototype to production-level systems, and support them once planners depend on them.
- Partner with the team's economists to connect forecasts with causal estimates of policy levers.
- Extend models to new sites, shifts, and business lines as the platform expands.
- Translate ambiguous business problems into modeling approaches, and drive the technical design with planning, engineering, and operations partners.

A day in the life
- Analyze data to investigate a forecast miss or model performance, and identify improvements
- Brainstorm modeling approaches with fellow scientists and economists on the team
- Build and backtest new features for your model
- Run a simulation or experiment to evaluate your model's performance
- Meet with planning, compensation, or finance partners to review requirements, data, design, or other project decisions
- Review code changes or a design document from a fellow scientist or engineer
- Write and present a document covering method, results, and recommendations

Basic Qualifications

- 3+ years of building models for business application experience
- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- Experience programming in Java, C++, Python or related language

Preferred Qualifications

- Experience using Unix/Linux
- Experience in professional software development
- Experience in building machine learning models for business application
- Experience in designing experiments and statistical analysis of results

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’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Pursuant to the San Francisco 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’re applying in isn’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 & 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 - 171,600.00 - 222,200.00 USD annually
USA, MA, Boston - 142,800.00 - 193,200.00 USD annually
USA, VA, Arlington - 142,800.00 - 193,200.00 USD annually
USA, WA, Bellevue - 142,800.00 - 193,200.00 USD annually
USA, WA, Seattle - 142,800.00 - 193,200.00 USD annually