Data Science Manager, PXT Central Science

Amazon

Bellevue, WA

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JOB DETAILS

SKILLS

Analysis Skills, Artificial Intelligence (AI), Auditing, Best Practices, Business Operations, Communication Skills, Computer Science, Computer Vision, Corporate Policies, Cross-Functional, Customer Support/Service, Data Modeling, Data Science, Economics, Emerging Technology, Engineering Management, Establish Priorities, Federal Laws and Regulations, Forecasting, Home Automation, Leadership, Machine Learning, Mathematics, Modeling Languages, Natural Language Processing (NLP), Performance Analysis, Performance Metrics, Predictive Modeling, Problem Solving Skills, Process Development, Process Improvement, Production Systems, Python Programming/Scripting Language, R Programming Language, Scientific Research, Scripting (Scripting Languages), Simulation, State Laws and Regulations, Statistical Modeling, Statistics, Strategic Planning, Team Lead/Manager, User Interface/Experience (UI/UX)

LOCATION

Bellevue, WA

POSTED

30+ days ago

Description 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 doesn't just describe what happened, but explains why it happened and predicts what comes next. That's the work we do. PXT Central Science (PXTCS) is Amazon's 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 Amazon's Tier 1 hourly populations - the associates at the heart of Amazon's operations. We are a multidisciplinary group of 15 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 don't 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 scientist who can help us push it forward. 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 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 - 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

About the Company

Amazon

At Amazon, we don’t wait for the next big idea to present itself. We envision the shape of impossible things and then we boldly make them reality. So far, this mindset has helped us achieve some incredible things. Let’s build new systems, challenge the status quo, and design the world we want to live in. We believe the work you do here will be the best work of your life.

Wherever you are in your career exploration, Amazon likely has an opportunity for you. Our research scientists and engineers shape the future of natural language understanding with Alexa. Fulfillment center associates around the globe send customer orders from our warehouses to doorsteps. Product managers set feature requirements, strategy, and marketing messages for brand new customer experiences. And as we grow, we’ll add jobs that haven’t been invented yet.

It’s Always Day 1
At Amazon, it’s always “Day 1.” Now, what does this mean and why does it matter? It means that our approach remains the same as it was on Amazon’s very first day – to make smart, fast decisions, stay nimble, invent, and stay focused on delighting our customers. In our 2016 shareholder letter, Amazon CEO Jeff Bezos shared his thoughts on how to keep up a Day 1 company mindset. “Staying in Day 1 requires you to experiment patiently, accept failures, plant seeds, protect saplings, and double down when you see customer delight,” he wrote. “A customer-obsessed culture best creates the conditions where all of that can happen.” You can read the full letter here

Our Leadership Principles
Our Leadership Principles help us keep a Day 1 mentality. They aren’t just a pretty inspirational wall hanging. Amazonians use them, every day, whether they’re discussing ideas for new projects, deciding on the best solution for a customer’s problem, or interviewing candidates. To read through our Leadership Principles from Customer Obsession to Bias for Action, visit https://www.amazon.jobs/principles

COMPANY SIZE

10,000 employees or more

INDUSTRY

Other/Not Classified

FOUNDED

1994

WEBSITE

http://Amazon.com/militaryroles