Lead Data Scientist

Data Scientist Lead - CDAO

Are you ready to turn complex data into clear, measurable progress? Join JPMorganChase’s Chief Data & Analytics Office, where you’ll help accelerate the firm’s data and analytics journey through high-impact insights and practical measurement solutions. You’ll work in a collaborative team that values curiosity, rigor, and continuous improvement. This is an opportunity to grow your influence while partnering across functions and presenting outcomes to senior leaders.

Job Summary:

As a Data Strategy Analytics Vice President within the Strategy and Execution team, you will develop insights and tracking mechanisms that support execution of our firmwide data strategy. You will partner with stakeholders to identify the right data across systems, design analyses and reporting, and synthesize actionable insights for senior leadership. You will combine statistical rigor with hands-on data science methods to build scalable telemetry and measurement solutions. You will contribute to a team culture that uses evidence to drive decisions and continuously improves how we measure impact.

Job Responsibilities

• Drive the development and delivery of data science solutions that measure progress against the firmwide data strategy.
• Partner with stakeholders to understand business processes, systems, and measurement needs.
• Identify, source, and integrate data across cloud and on-premise environments to support strategic analytics.
• Design and deliver analyses and models that produce structured, decision-ready insights.
• Build and maintain dashboards and visualization tools that track telemetry and progress.
• Develop machine learning solutions that automate telemetry and measurement workflows.
• Present findings clearly through written narratives and presentations tailored to the audience.
• Apply statistical rigor, testing, and validation practices to ensure trustworthy results.
• Monitor emerging AI/ML/LLM/GenAI trends and evaluate practical applications to measurement and insight delivery.
• Improve existing analytics products through iteration, feedback, and performance monitoring.

Required Qualifications, Capabilities, and Skills

• 5 years of experience as a data scientist or in an adjacent quantitative role.
• Demonstrated experience delivering end-to-end analytics or data science solutions from problem framing through insight delivery.
• Foundational knowledge of supervised and unsupervised machine learning techniques.
• Proficiency in Python, R, or an equivalent programming language for data analysis and modeling.
• Experience working with structured and/or unstructured data across multiple sources.
• Ability to translate complex analysis into clear, actionable recommendations for technical and non-technical audiences.
• Strong problem-solving skills and structured thinking in ambiguous environments.
• Strong written and verbal communication skills, including presenting to senior stakeholders.
• Strong collaboration skills and ability to work effectively across teams.

Preferred Qualifications, Capabilities, and Skills

• Experience developing and implementing machine learning solutions in AWS or another cloud platform.
• Familiarity with machine learning engineering concepts (e.g., deployment patterns, monitoring, automation).
• Familiarity with financial services data, products, or operating environments.

 

Experience Level

Senior Level