Join our team as a Data Science Manager (AI Products) where you'll lead a high-impact team of data scientists in developing software products powered by machine learning and AI. You'll be responsible for building our underlying platform capabilities, creating personalized voice and digital experiences, and driving measurable growth for our stakeholders. This role requires a player-coach who can architect and build alongside their team while providing leadership, direction, and mentorship.
About the role
- A proven track record delivering production data science solutions using machine learning and/or generative AI - Business acumen and a track record of translating open-ended partner and customer problems into shipped ML solutions, recommendation systems, LLM-driven personalization, agentic products, supervised models of customer behavior, that drive acquisition, retention, and operational outcomes - Comfort balancing technical depth with clear communication, writing and reviewing code while also scoping work, aligning stakeholders, and supporting team growth - Solid understanding of the ML/LLM lifecycle and LLMOps/MLOps concepts, including deployment, monitoring, and iteration in production environments—with hands-on experience using tools such as LangSmith, MLflow, or similar platforms. Familiarity with AI-assisted development tools such as Claude Code is a plus - Hands-on experience building LLM-based and agentic AI systems, with fluency in orchestration frameworks such as LangChain, LangGraph, Mastra, OpenAI Agents SDK, or similar tools - Familiarity with the broader modern AI stack, including large language model providers (e.g., OpenAI, Gemini, Claude) and cloud AI infrastructure such as AWS Bedrock AgentCore - Bachelor’s Degree + 8 years of experience OR Master’s Degree + 6 years of experience OR PhD + 4 years of experience - Prior experience leading or mentoring data scientists, with an interest in growing others while remaining technically engagedKey missions
- Lead a team of data scientists in developing software products powered by machine learning and AI.
- Architect and build end-to-end AI/ML and agentic solutions, overseeing the entire lifecycle from prototype to deployment.
- Collaborate with cross-functional teams to shape and deliver data science initiatives aligned with organizational strategy.