Associate, Data Analytics, Commercial & Investment Bank, Tech Strategy and Execution
About The Position
JPMorgan Chase’s Commercial & Investment Bank (CIB) is seeking an Associate on our AI for Tech initiative. Our firm, and CIB in particular, is investing heavily into AI tooling and adoption in the software engineering lifecycle. You will design, build, and produce analysis to quantify our software engineering throughput, understand its business outcomes, and the contribution of GenAI to these outcomes. This product will directly support our culture change efforts for AI usage by software engineers. This analysis will help guide our efforts to drive cultural transformation through data driven evidence and insights. As a Strategy Associate in our CIB Tech Strategy and Execution team, you will have a hands-on builder role operating at the intersection of strategy, engineering, and data. You will own core parts of the data foundation while working iteratively to turn ambiguous questions into scalable data and insight. In addition to measurement work, you will have the flexibility to support other AI for Tech strategic priorities as business needs evolve. This role requires a mix of quantitative problem solving, data engineering skills, and analytical curiosity to use data to shape organizational change management. Your analytical insights and outputs will be consumed by the most senior leaders of CIB’s technology organization.
Requirements
- Bachelor’s or Master’s degree in a quantitative or technical field (e.g. Computer Science, Data Science, Mathematics, Statistics)
- Extensive hands-on experience with Python, SQL, Spark, Databricks building and maintaining data ingestion and transformation pipelines
- Experience with data visualization tools such as Tableau, Sigma, Qlikview
- Strong Excel data modelling skills
- Fluency in software engineering and domain understanding of the software development lifecycle (SDLC)
- Strong problem-solving skills to work from ambiguous open-ended questions, and communicate clearly to senior stakeholders
Nice To Haves
- Preferred background in data analytics / engineering within a strategy or consulting context
Responsibilities
- Build and maintain scalable data ingestion and transformation pipelines that connect source engineering systems into an analytical foundation
- Design and evolve the engineering measurement data model, ensuring it accurately reflects how software is delivered across teams
- Drive improvements in data quality, consistency, and definition alignment across multiple engineering data sources
- Develop metrics and analyses from data, pressure-testing them with engineers to ensure measurement reflects real delivery behavior
- Translate requirements into concrete analytical deliverables that can be iterated quickly as leadership priorities evolve
- Engage technology and business stakeholders across Markets, Payments, Security Services, and Global Banking to ensure measurement outputs reflect the needs of different customer groups
- Partner closely with engineers, data scientists, and central global technology teams
- Support vendor strategy decisions
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Mid Level
