Senior Data Scientist, GTM Strategy & Transformation
Company: Red Hat
Location: Raleigh, NC (Remote)
Type: Full-time
Remote: Yes
Posted: 2026-05-08
About this role
Red Hat’s Global Sales Go-To-Market (GTM) team is looking for a high-impact Principal Data Scientist to bridge the gap between complex data architecture and executive strategy. This isn’t a "maintenance" role—you will be an architect of change, leveraging AI, advanced statistics, and a builder’s mindset to reinvent how we handle quotas, incentives, and sales capacity.
We need a hybrid talent: someone with the technical depth to code automated pipelines from scratch and the business savvy to translate those results into a "digestible story" for executive leadership.
What You Will Do
- Architect from Scratch: Design and deploy end-to-end automated processes for the quota and incentive lifecycle, ensuring bulletproof data validation
- Scale AI Integration: Use advanced prompt engineering and LLM tools to accelerate development, audit code, and eliminate manual workflows
- Master the Pipeline: Extract and enrich massive datasets from Snowflake and GitHub, ensuring data integrity across complex logic layers
- Tell the Story: Translate highly technical outputs into strategic recommendations. You will present key performance metrics directly to executive leadership
- Solve the "Puzzle": Apply predictive modeling and pattern recognition to evaluate sales coverage and optimize customer engagement at scale
What You Will Bring
- Programming: Mastery of Python (Pandas, Google Cloud libraries) and SQL (Snowflake/DBeaver)
- AI Fluency: You treat AI as a primary collaborator, using prompt engineering to increase your velocity
- Statistics: Deep knowledge of regression, simulation, scenario analysis, clustering, and decision trees
- Data Ops: Experience with GitHub workflows and building "self-healing" scripts to prevent recurring data errors
- Visualization: Ability to build impactful narratives in Tableau, Google Sheets, and Salesforce CRMA
- Experience: 10+ years of professional experience manipulating large datasets and building production-grade statistic...