Strategic Insights Lead, Data Science & AI

JPMorgan Chase & Co.

Columbus (OH)

On-site

USD 140,000 - 190,000

Full time

10 days ago

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Job summary

JPMorgan Chase & Co. in Columbus seeks a Data Science Lead within PXT Data & Analytics to drive 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, and partner with execution teams to assign actions and timelines. You will lead a team, track adoption and outcomes, and set standards for analytical quality and responsible data/AI

Qualifications

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.

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.