Strategic Insights Data Science Lead

JPMorganChase; Chicago (IL); On-site; USD 128,000 - 200,000; Full time

Job summary

JPMorganChase in Chicago seeks a Strategic Insights Data Science Lead to shape how AI transforms product development productivity across Product Operations, Experience, Technology, and Data & Analytics teams. You will lead a high-velocity analytics effort to test hypotheses, identify best practices, and translate evidence into actionable steps for senior leaders.

You will guide a team to turn ambiguous productivity questions into decision-ready findings, partnering with executives to implement

Qualifications

• Bachelor’s degree in quantitative field with 5+ years data science/analytics experience.
• Experience leading analytical work from problem framing through implementation and outcome measurement.
• Strong hypothesis development, experimental design, quantitative analysis, synthesis, and problem-solving skills.
• Proficiency with Python, SQL, large datasets, modern analytics platforms, and visualization tools.
• Understanding of product development workflows and productivity metrics, including cycle time, throughput, quality, capacity, and adoption.
• Ability to work at pace in ambiguous environments, balancing analytical rigor with practical decision-making.
• Proven ability to influence senior stakeholders, lead analytical talent, and translate complex findings into clear actions and measurable outcomes.

Responsibilities

• Lead high-velocity, hypothesis-driven analysis of Product Operations and product development productivity.
• Turn ambiguous questions about operating models, workflows, and AI adoption into focused analytical plans and decision criteria.
• Assess how AI tools and ways of working affect delivery speed, quality, capacity, and value.
• Combine product, delivery, and AI adoption data with stakeholder context to identify actionable opportunities.
• Produce decision-ready briefs with clear findings, recommendations, owners, timelines, benefits, and guardrails.
• Partner across Product Operations, Product, Technology, and Finance to implement recommendations and track adoption and outcomes.
• Set standards for analytical quality, productivity measurement, executive communication, and responsible use of data and AI.
• Develop and manage a high-performing team and influence senior leaders with clear, practical insights.

Skills

Data science

Analytical mindset

Problem solving

Python

SQL

Stakeholder influence

Leadership

Education

Bachelor’s degree in quantitative discipline

Tools

Python

SQL

Job description

Strategic Insights Data Science Lead

1111 Polaris Pkwy, Columbus, OH, 43240, US

880 Powder Mill Rd, Wilmington, DE, 19803, US

10 S Dearborn St, Chicago, IL, 60603, US

Job Schedule Full time

Base Pay/Salary Chicago,IL $128,250.00-$200,000.00

Job Description

Help shape how Chase improves product development productivity as AI transforms the way Product, Experience, Technology, and Data & Analytics teams work. You will lead a Strategic Insights team that rapidly tests hypotheses, identifies effective operating practices and AI-enabled workflows, and translates evidence into clear actions for Product Operations and Finance leaders.

As a Data Science Lead within Product, Experience, and Technology (PXT) Data and Analytics at JPMorganChase, you will lead high-velocity analysis of operating-model changes, product practices, and AI tools across the product development lifecycle. You will turn ambiguous productivity questions into decision-ready findings and recommendations, partner with execution teams to assign actions and timelines, and track adoption and outcomes.

Job responsibilities

• Lead high-velocity, hypothesis-driven analysis of Product Operations and product development productivity


• Turn ambiguous questions about operating models, workflows, and AI adoption into focused analytical plans and decision criteria


• Assess how AI tools and ways of working affect delivery speed, quality, capacity, and value


• Combine product, delivery, and AI adoption data with stakeholder context to identify actionable opportunities


• Produce decision-ready briefs with clear findings, recommendations, owners, timelines, benefits, and guardrails


• Partner across Product Operations, Product, Technology, and Finance to implement recommendations and track adoption and outcomes


• Set standards for analytical quality, productivity measurement, executive communication, and responsible use of data and AI


• Develop and manage a high-performing team and influence senior leaders with clear, practical insights

Required qualifications, capabilities and skills

• Bachelor’s degree in quantitative discipline and 5+ years of applied data science or analytics experience


• Experience leading analytical work from problem framing through implementation and outcome measurement


• Strong hypothesis development, experimental design, quantitative analysis, synthesis, and problem-solving skills


• Proficiency with Python, SQL, large datasets, modern analytics platforms, and visualization tools


• Understanding of product development workflows and productivity metrics, including cycle time, throughput, quality, capacity, and adoption


• Ability to work at pace in ambiguous environments, balancing analytical rigor with practical decision-making


• Proven ability to influence senior stakeholders, lead analytical talent, and translate complex findings into clear actions and measurable outcomes

Preferred qualifications, capabilities and skills

• Experience building or leading a consulting-style strategic analytics or insights team


• Experience in product operations, product management, technology delivery, organizational effectiveness, or financial services


• Experience evaluating operating-model changes, workflow redesign, or enterprise productivity initiatives


• Experience with experimentation, causal inference, forecasting, optimization, machine learning, or natural language processing


• Experience evaluating or deploying Generative AI and agentic tools in operational workflows, including adoption, telemetry, quality, risk, cost, and value realization


• Familiarity with product development lifecycle data and tools used to manage requirements, backlogs, dependencies, code, testing, and delivery


• Demonstrated success creating executive briefs and operating mechanisms that drive decisions, ownership, adoption, and follow-through


• Master’s degree, MBA, PhD, or equivalent advanced degree

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