Manager III, Applied Science, PXT Central Science

Every day hundreds of thousands of Amazon associates show up to fulfill the promise we make to our customers. Behind the workforce decisions that support them staffing retention scheduling development there should be science that doesnt just describe what happened but explains why it happened and predicts what comes next. Thats the work we do.

PXT Central Science (PXTCS) is Amazons internal research organization dedicated to bringing scientific rigor to people and workforce decisions at global scale. Our team sits within the part of PXTCS that focuses on Amazons Tier 1 hourly populations the associates at the heart of Amazons operations. We are a multidisciplinary group of economists data scientists data engineers and research scientists united by a single mission: to transform complex operational challenges into actionable insights through rigorous causal analysis and predictive modeling that empowers data-driven workforce decisions.

We are building something new causal predictive models that go beyond traditional forecasting. Our models dont just tell leaders what will happen; they reveal why it will happen and what levers they can pull to change the outcome. This is the frontier where causal inference meets modern machine learning and we need a leader who can build and guide the team that pushes it forward.

As an Applied Science Manager on this team you will own both the scientific vision and the people strategy for our applied science function. You will lead a diverse team of scientists working at the intersection of causal inference and machine learning setting the technical direction raising the bar on modeling and engineering practices and ensuring that research translates into production systems that leaders use to make better workforce decisions every day. You will work closely with economists who deeply understand the causal mechanisms driving workforce dynamics data scientists who know the operational landscape and a dedicated partner engineering team that productionizes your teams work.

This is not a role where you manage from a distance. You will stay close to the science reviewing model designs shaping feature engineering strategies and guiding your team through the ambiguity of novel problem spaces including large language models computer vision and other emerging techniques applied to workforce challenges. At the same time you will build the team culture operating mechanisms and talent pipeline needed to scale our applied science capabilities as the organization grows.

This role is built for someone who is both a strong technical scientist and a genuine people leader someone who gets energy from developing others who can translate between disciplines and who sees building a high-performing team as one of the most impactful things they can do. You will partner with stakeholders and senior leadership to define priorities communicate results and drive the adoption of science-informed workforce strategy across Amazons operations.

If you want to lead a team doing science that directly shapes how Amazon supports its workforce not in theory but in production systems that drive real decisions at scale wed love to talk.

Key job responsibilities
Manage and develop a high-performing team of scientists fostering innovation and scientific rigor while providing coaching mentorship and clear growth paths
Establish operating mechanisms and performance expectations to track and communicate team progress
Own hiring and talent strategy for the applied science function including hiring and conversion for other job families
Set and execute the scientific vision for the applied science function bringing deep ML expertise to the teams causal predictive modeling agenda and identifying where advanced methods (deep learning LLMs computer vision novel architectures) can strengthen the causal frameworks and unlock signal that traditional approaches miss
Establish standards for code quality documentation and scalability to ensure your teams work can be implemented directly into operational decision-making tools by partner engineering teams
Bridge economists data scientists research scientists and engineers synthesizing causal rigor with ML innovation to produce models that are scientifically defensible and operationally useful
Partner with stakeholders and senior leadership to define priorities drive adoption of science-informed workforce strategy and leverage the broader scientific community
Distill complex causal and predictive findings into clear recommendations for senior leadership that drive workforce strategy for Amazons hourly populations
Define team structure strategic direction and owned technologies adjusting priorities and removing roadblocks to optimize outcomes

About the team
Amazons People Experience and Technology Central Science (PXTCS) team uses economics behavioral science statistics machine learning applied science 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 engineering and UX to develop and deliver solutions that measurably achieve this goal.

- 3 years of scientists or machine learning engineers management experience
- Knowledge of ML NLP Information Retrieval and Analytics

- Experience building machine learning models or developing algorithms for business application
- Experience building complex software systems especially involving deep learning machine learning and computer vision that have been successfully delivered to customers

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 Companys 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 for more information. If the country/region youre applying in isnt 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 CA San Francisco - 211400.00 - 286000.00 USD annually
USA VA Arlington - 183800.00 - 248700.00 USD annually
USA WA Seattle - 183800.00 - 248700.00 USD annually