We are looking for an Applied Scientist who will serve as a force multiplier across our customer engagement teams, building the analytical foundations, predictive models, and reusable tooling that power our go-to-market strategy. You will work at the intersection of data science, machine learning, and business strategy, building models that quantify our value proposition, and creating scalable analytical assets that accelerate every engagement. This is a highly visible, high-impact role where your work directly influences how we demonstrate and measure the value of AWS AI solutions for enterprise customers.

You will operate with significant autonomy, owning the scientific direction of your projects while collaborating with software engineers, product managers, and business stakeholders. You will identify the right methodology for each problem, whether that is a classical statistical approach, a modern deep learning technique, or a novel combination, and communicate your findings clearly to both technical and non-technical audiences. This role spans Connect Customer initiatives and across the Applied AI solution portfolio, offering the opportunity to pioneer data science approaches that scale intelligent analytics worldwide.

If you thrive at the intersection of rigorous science and customer-facing impact and are energized by translating complex model outputs into business decisions, we want to talk to you.

Key job responsibilities

Design, develop, and deploy statistical models and machine learning pipelines to drive product improvements, business decisions, and customer outcomes

Work directly with customers during production pilots to build and deploy AI solutions that demonstrate measurable business value

Design and execute A/B experiments and causal inference analyses to measure the impact of new features and model changes

Build ROI models, business case tools, and forecasting systems for demand prediction, capacity planning, workforce optimization, and value quantification

Apply NLP and generative AI techniques to extract insights from structured and unstructured data at scale, and partner with software engineers to productionize models with reliability, monitoring, and operational excellence

Build and own customer analytics capabilities including segmentation (by size tier, AI adoption, product penetration, entitlement), usage trend analysis, propensity modeling, and foundational datasets combining service usage with sales data

Create self-service analytics platforms and automated insight delivery mechanisms that enable leadership to pull strategic intelligence on demand

Enable field teams with reusable analytical assets, diagnostic notebooks, benchmarking studies, and scalable tooling that accelerate customer engagements

Own success metrics and create mechanisms to measure model performance, adoption, and business impact across customer cohorts

Define strategic frameworks and GTM recommendations by segment, translating data patterns and market signals into actionable go-to-market motions and investment priorities

Communicate findings and technical trade-offs to senior leadership and customer executives through written documents (6-pagers, science reviews) and presentations, operating as a shared resource across 2-3 teams simultaneously

BASIC QUALIFICATIONS

- PhD, or Master's degree and 6+ years of applied research experience

- 5+ years of building machine learning models for business application experience

- Experience with neural deep learning methods and machine learning

- Experience managing analytics, data science or technology teams, with a product or insight focus

- Experience working with diverse or differing data sets including creating and compiling data into a final distribution for management consumption

- Experience with customer segmentation, profiling, and targeting

PREFERRED QUALIFICATIONS

- PhD

- Track record of delivering end-to-end data science solutions from problem definition through production deployment

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, Mountain View - 192,200.00 - 260,000.00 USD annually

USA, CA, San Francisco - 192,200.00 - 260,000.00 USD annually

USA, IL, Chicago - 167,100.00 - 226,100.00 USD annually

USA, NY, New York - 183,800.00 - 248,700.00 USD annually

USA, TX, Austin - 167,100.00 - 226,100.00 USD annually

USA, TX, Dallas - 167,100.00 - 226,100.00 USD annually

USA, VA, Herndon - 167,100.00 - 226,100.00 USD annually

USA, WA, Seattle - 167,100.00 - 226,100.00 USD annually