Senior Applied Scientist, Applied AI Solutions GTM

AWS Applied AI Solutions (AAIS) seeks an Applied Scientist to build analytical foundations, predictive models, and reusable tooling that power our go‑to‑market strategy. The role operates at the intersection of data science, machine learning, and business strategy, directly influencing how we demonstrate and measure the value of AWS AI solutions for enterprise customers.

• 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, partnering with software engineers to product ionize models with reliability, monitoring, and operational excellence.
• Build and own customer analytics capabilities including segmentation, 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 and presentations, operating as a shared resource across 2‑3 teams simultaneously.

• PhD, or Master's degree and 6+ years of applied research experience.
• 5+ years of building machine learning models for business application.
• 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.

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

The base salary range for this position varies by location:

• Mountain View, CA: 192,200 – 260,000 USD annually
• San Francisco, CA: 192,200 – 260,000 USD annually
• Chicago, IL: 167,100 – 226,100 USD annually
• New York, NY: 183,800 – 248,700 USD annually
• Austin, TX: 167,100 – 226,100 USD annually
• Dallas, TX: 167,100 – 226,100 USD annually
• Herndon, VA: 167,100 – 226,100 USD annually
• Seattle, WA: 167,100 – 226,100 USD annually

AWS is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.