Lead Data Analytics Engineer - Global Technology Analytics, Insights and Metrics

Based in New York, JPMorgan Chase offers an onsite leadership role within the Global Technology Analytics, Insights and Metrics (GT AIM) team to turn data into decision-grade insights across technology domains. The position focuses on delivering transparent analytics that inform technology strategy and investment decisions, with a salary range of USD 204,250 to 285,000 per year.

Responsibilities

• Build and maintain a metrics framework complemented by visuals that align with CTO and technology leadership decision needs, spanning initiatives from AI to software engineering and portfolio management.
• Foster strong relationships across GT functions and convey statistical findings clearly to both technical and non-technical audiences, avoiding oversimplification while communicating what is happening, why it matters, and the level of confidence.
• Collaborate on JPMorgan Chase strategic programs, providing ongoing analysis and insights with sound statistical measures to support priority outcomes, explaining performance, trends, variability, and drivers across all GT.
• Lead and develop a small team of analytics professionals, establishing and upholding standards for statistical rigor, transparency and clarity.
• Continuously refine analytic approaches as technology strategy, architecture, and delivery practices evolve, helping technology leadership understand trade-offs, risks, opportunities and uncertainty.
• Ensure conclusions are statistically and contextually valid, grounded in engineering and business ecosystems; work with engineering, platform, architecture and AI enablement teams to understand delivery practices, workflows and constraints.
• Perform hands-on statistical analysis using descriptive, inferential and exploratory techniques, applying them to assess variability, confidence, uncertainty, statistical significance and margin of error where appropriate.
• Evaluate distributions, trends and changes over time while accounting for structural differences in teams, systems and delivery models; distinguish correlation from causation and clearly communicate analytical limitations, assumptions and confidence levels.

Requirements

• Degree in Mathematics, Statistics, Data Science, Engineering, Computer Science or equivalent with 7+ years of applicable work experience.
• 10+ years of experience performing statistical analytics, data science or performance measurement roles.
• Practical experience working with technology, delivery, portfolio, financial or AI-related data.
• Proven ability to apply statistical methods to real-world, imperfect datasets and evolving delivery practices.
• Strong familiarity with statistical significance, confidence intervals, variability and margin of error, and appropriate usage contexts.
• Proficiency in a modern data stack, including Excel, Python, R Studio, Power BI, Tableau, Qlik, SQL, dbt, Databricks, Snowflake, Microsoft Fabric, and Apptio for portfolio and spend analytics.
• Demonstrated proficiency in software applications and technical processes within a technical discipline (cloud, artificial intelligence, machine learning, mobile, etc.).
• Experience influencing senior technology leaders and guiding decision-making.

Technologies

• Excel
• Python
• R Studio
• Power BI
• Tableau
• Qlik
• SQL
• dbt
• Databricks
• Snowflake
• Microsoft Fabric
• Apptio

Benefits

• comprehensive health care coverage
• on-site health and wellness centers
• retirement savings plan
• backup childcare
• tuition reimbursement
• mental health support
• financial coaching