Senior Applied Scientist, Applied AI Solutions GTM
About the role
AWS Applied AI Solutions (AAIS) is dedicated to making AI accessible to enterprises. We develop and deploy AI solutions that yield tangible business outcomes at scale, collaborating with applied scientists, AI architects, business development professionals, and GTM specialists.
Responsibilities
Design, develop, and deploy statistical models and machine learning pipelines to enhance product performance, inform business decisions, and improve customer outcomes.
Collaborate with customers during production pilots to build and implement AI solutions that showcase measurable business value.
Execute A/B experiments and causal inference analyses to assess the impact of new features and model modifications.
Create ROI models, business case tools, and forecasting systems for demand prediction, capacity planning, workforce optimization, and value quantification.
Utilize NLP and generative AI techniques to derive insights from structured and unstructured data at scale, and integrate these insights into production-ready models.
Build and maintain customer analytics capabilities, including segmentation, usage trend analysis, propensity modeling, and integrated datasets combining service usage with sales data.
Develop self-service analytics platforms and automated insight delivery mechanisms to facilitate strategic intelligence for leadership.
Support field teams with reusable analytical assets, diagnostic notebooks, benchmarking studies, and scalable tooling to expedite customer engagements.
Establish and monitor success metrics, assessing model performance, adoption, and business impact across different customer segments.
Formulate strategic frameworks and GTM recommendations by segment, translating data insights into actionable go-to-market strategies and investment priorities.
Communicate findings and technical trade-offs to senior leadership and customer executives through written reports and presentations.
Requirements
PhD or Master's degree with 6+ years of applied research experience
5+ years of experience building machine learning models for business applications
Experience with neural deep learning methods and machine learning
Experience managing analytics, data science, or technology teams, with a focus on products or insights
Experience with diverse or varied data sets, including data compilation for management consumption
Experience with customer segmentation, profiling, and targeting
Qualifications
PhD preferred
Track record of delivering end-to-end data science solutions from problem definition to production deployment