Senior Applied Scientist, Applied AI Solutions GTM

Amazon • Austin, TX

22h • $167,100 - $260,000 • Hybrid

About The Position

Amazon Web Services (AWS) Applied AI Solutions (AAIS) is focused on making AI a reality for enterprises by building and deploying production AI solutions that deliver measurable business outcomes at scale. The GTM Acceleration team within AAIS is responsible for activating the field, measuring impact, and scaling successful initiatives. This team acts as a crucial link between AAIS product/science teams and the global field organization, ensuring effective customer reach, quantifying delivered value, and establishing globally scalable repeatable processes. The role of an Applied Scientist is to serve as a force multiplier for customer engagement teams by developing analytical foundations, predictive models, and reusable tools to support the go-to-market strategy. This position operates at the intersection of data science, machine learning, and business strategy, focusing on building models to quantify value propositions and creating scalable analytical assets to enhance customer engagements. It's a high-visibility, high-impact role directly influencing how AWS AI solutions' value is demonstrated and measured for enterprise customers. The scientist will work with significant autonomy, guiding project scientific direction while collaborating with software engineers, product managers, and business stakeholders. They will select appropriate methodologies, from classical statistics to deep learning or novel combinations, and effectively communicate findings to both technical and non-technical audiences. This role supports Connect Customer initiatives and the broader Applied AI solution portfolio, offering opportunities to pioneer data science approaches for scaling intelligent analytics globally. The ideal candidate thrives at the intersection of rigorous science and customer-facing impact, and is adept at translating complex model outputs into actionable business decisions.

Requirements

• 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

Nice To Haves

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

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

Benefits

• 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
• parental leave
• sign-on payments
• restricted stock units (RSUs)

What This Job Offers

• Job Type: Full-time
• Career Level: Senior