Senior Applied Scientist, Applied AI Solutions GTM
About the role
AWS Applied AI Solutions (AAIS) is dedicated to making AI accessible for enterprises. We develop and deploy AI solutions that yield tangible business benefits at scale, collaborating with scientists, architects, business developers, 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 design and implement AI solutions that showcase measurable business value.
Execute A/B tests and causal inference analyses to assess the impact of new features and model updates.
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 analyze structured and unstructured data at scale, and integrate these models into production environments with reliability and operational excellence.
Develop customer analytics capabilities such as segmentation, usage trend analysis, propensity modeling, and combine service usage with sales data to provide foundational datasets.
Build and maintain self-service analytics platforms and automated insight delivery mechanisms to enable leaders to access strategic intelligence swiftly.
Support field teams by providing reusable analytical assets, diagnostic notebooks, benchmarking studies, and scalable tooling to expedite customer engagements.
Track and evaluate success metrics, including model performance, adoption rates, and business impact across different customer segments.
Formulate strategic frameworks and GTM recommendations tailored to specific customer segments, translating data insights into actionable go-to-market strategies and investment priorities.
Communicate findings and technical considerations to senior leadership and customer executives through various formats, including 6-page 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 leading analytics, data science, or technology teams, focusing on products or insights
Experience managing diverse or varied data sets, including compiling them into consumable forms for management
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