Lead Data Scientist

On-siteSeniorData Scientistposted 4d ago

✦Role summaryAI-generated

Lead a small team of data scientists to develop and execute analytics for onboarding and engagement marketing campaigns at JPMorgan Chase. Drive data‑driven decisions that optimize multimillion‑dollar marketing investments and strengthen long‑term customer relationships.

Skills required

Python SQL Machine learning Statistical modeling Data visualization Cohort analysis A/B testing Predictive modeling Marketing analytics Data pipelines Agentic AI AI Recommendation systems Data science Statistics R

About this role

Vice President – Consumer Bank Marketing Analytics (Onboarding & Engagement)

As the Onboarding & Engagement Analytics Team Lead in Consumer Bank Marketing Analytics, you’ll own the analytics strategy behind onboarding and engagement marketing campaigns and lead a team in turning data into decisions that strengthen long-term customer relationships and optimize multimillion-dollar marketing investments.

Job Responsibilities:

Lead a team of three to four data scientists developing and executing the analytics roadmap to drive Onboarding and Engagement marketing strategy while also being a hands-on-contributor.
Translate unstructured business questions into rigorous customer behavior analyses. Identify gaps in how we measure, target, or engage customers today and lead the work to close them
Lead A/B and incrementality testing from experimental design through interpretation and recommendation
Design and influence the build of reusable data products, including curated data sets, context libraries, and AI agents, that power both analyst-led insights and emerging agentic AI solutions
Present findings and recommendations to senior stakeholders
Partner with leaders in Data & Analytics, Finance, and Marketing on experimental design and data strategy

Required qualifications, capabilities and skills:

Master’s degree in quantitative discipline (Data Science/Analytics, Mathematics, Statistics, Engineering, Economics, Finance, or related field), OR equivalent directly applicable experience
2+ years of direct or indirect people management experience, including hiring, training and developing high-performing talent.
4+ years applying statistical methods to real-world problems
4+ years of SQL experience; proficiency in Python or R; and experience with data visualization tools and techniques.
Hands-on experience with AI tools (e.g., GitHub Copilot, Claude Code, Codex) to accelerate day-to-day analytics; experience developing agents
Strong written and verbal communication skills, with experience articulating results to all levels of management.