VP Data Science Lead — Wealth & AI Strategy

Socket.dev; New York (NY); On-site; USD 150,000 - 230,000; Full time

Job summary

JPMorganChase is seeking a Data Science Lead in Wealth Management Decision Sciences to lead a team delivering insights and machine learning solutions that improve client outcomes, product performance, and operational efficiency. You will partner with product, strategy, and operations to frame problems, define success measures, and deliver clear recommendations to senior stakeholders.

This hands-on managerial role requires blending descriptive analytics with advanced modeling, building scalable

Qualifications

• BS degree in a STEM field with 5+ years analytics experience.
• 2 years of people management experience, including coaching and team development.
• Led data science teams to deliver analytics and ML solutions that improve business performance.

Responsibilities

• Collaborate with product, strategy, and operations to support wealth management decisions.
• Apply statistics and AI approaches to solve business problems across product, financial, client engagement, and operational outcomes.
• Lead end-to-end analytics delivery from framing and measurement design to senior stakeholders.
• Develop analytics approaches for ML and trigger capabilities to improve operations in a scalable way.
• Analyze client usage across risk segments to understand portfolio allocations.
• Operationalize experimentation frameworks to quantify impact and inform prioritization.
• Assess client experience and AI-enabled discovery to identify measurable value creation.
• Identify AI and agentic use cases to improve productivity and decision quality.

Skills

Analytics leadership

Data science

Machine learning

Statistical methods

SQL PySpark

Communication

Education

BS Degree in STEM

Tools

SQL

PySpark

Jupyter

Job description

JPMorganChase is seeking a Data Science Lead in Wealth Management Decision Sciences to lead a team delivering insights and machine learning solutions that improve client outcomes, product performance, and operational efficiency. You will partner with product, strategy, and operations to frame problems, define success measures, and deliver clear recommendations to senior stakeholders.

This hands-on managerial role requires blending descriptive analytics with advanced modeling, building scalable