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Lead Software Engineer - Global Technology Analytics, Insights and Metrics

Job in New York, New York County, New York, 10261, USA
Listing for: J.P. Morgan
Full Time position
Listed on 2026-02-01
Job specializations:
  • IT/Tech
    Data Science Manager, AI Engineer
Salary/Wage Range or Industry Benchmark: 100000 - 125000 USD Yearly USD 100000.00 125000.00 YEAR
Job Description & How to Apply Below
Location: New York

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.

As a Lead Software Engineer at JPMorgan

Chase within the Global Technology - Analytics, Insights and Measurements (GT AIM) team, you will deliver trusted, decision-grade insight across GT through rigorous statistical analysis and domain-informed interpretation. You will be entrusted in delivering market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.

Reporting to the Head of GT Architecture and Strategy (GTAS), this role applies sound statistical and analytical methods to technology data to inform strategy, execution, and investment decisions across multiple technology domains. The role works in close partnership with leaders of strategic programs, providing continuous statistical analysis and insight to support priority outcomes.

The role requires deep understanding of software engineering delivery models and flows e.g., feature branch, trunk-based, and integrated delivery to ensure metrics and analysis accurately reflect how technology is delivered. Areas of focus include developer productivity, delivery and portfolio performance, technology spend and value realization, return on investment, and the adoption and impact of Artificial Intelligence across GT.

The emphasis is on building internally owned, transparent, and explainable analytics through sound statistical methods, rather than relying on opaque third‑party tools. All roles are hands‑on. Managers provide leadership and direction while actively contributing to analysis and insight delivery. Senior Individual Contributors independently own complex analytical problems and influence outcomes through expertise and insight.

Job responsibilities

Insights, Communications and Reporting
  • Define, create, deliver, establish and maintain a metrics framework and complementary visuals aligned to CTO and technology leadership decision needs. Your framework will be inclusive of many different technology initiatives, including emerging capabilities such as Artificial Intelligence (AI), Software Engineering, Portfolio Management and more.
  • Build strong relationships across various GT functions. Communicate statistical findings effectively to technical and non‑technical audiences without oversimplification or false precision. Narratives and analyses need to be clear. They need to articulate what is happening, why it is happening, and how confident the conclusions are.
  • Work closely to JPMC key strategic programs and initiatives, while providing continuous analysis & insights to support their priority outcomes, all with sound statistical measures. Your insights must explain performance, trends, variability, and drivers across all of GT.
Statistical Analysis and Data Interpretation
  • Continuously refine analytical approaches as technology strategy, architecture, and delivery practices evolve. Support technology leadership in understanding trade‑offs, risks, opportunities, and uncertainty.
  • Conclusions provided must be sound, statistically and contextually valid and based on actual engineering and business ecosystems. Collaborate closely with engineering, platform, architecture, and AI enablement teams to understand delivery practices, workflows and constraints.
  • Perform hands‑on statistical analysis using appropriate descriptive, inferential, and exploratory techniques. Apply those techniques and reasoning 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. Be able to distinguish correlation from causation and clearly communicate analytical limitations, assumptions, and confidence levels.
Operations, Measurements and Instrumentation
  • Identify required data points needed to answer key analytical and statistical questions, then define…
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