VP Data Scientist Lead – Product, Experience and Technology (PXT) Analytics Team

JPMorgan Chase & Co. • New York, NY

9h

About The Position

Join us to shape how we measure and improve the software delivery experience
across Chase.  You will lead a team that turns product and engineering data into
clear, trusted insights that influence strategy, investment decisions, and
roadmaps.  This role offers the opportunity to define measurement frameworks in
an area where standards are still evolving, and to build a culture of analytical
rigor and practical impact.  If you enjoy ambiguous problems, influencing senior
stakeholders, and developing talent, you will thrive with us.

Job summary 

As a Vice President, Data Science Lead in the Product, Experience and Technology
Analytics team, you will define and execute the analytics strategy that measures
developer productivity, technology efficiency, and product value across internal
platforms and tools.  You will lead data scientists and analysts to build
measurement frameworks, dashboards, and models that quantify adoption,
engagement, and outcomes across the software development lifecycle.  You will
partner closely with leaders across Product, Technology, and Finance to
translate complex findings into clear narratives that drive decisions.  You will
set priorities, raise the bar on analytical rigor, and help your team deliver
high-impact insights at scale.

Our analytics work focuses on initiatives that improve software delivery and
developer workflows, including measurement of CI/CD enhancements and adoption
and impact of generative AI solutions embedded in engineering processes.  You
will help establish consistent definitions and reporting for metrics such as
cycle time, throughput, and product adoption funnels, enabling leaders to
understand what is working and where to invest next.

Requirements

• Bachelor’s degree in data science, statistics, computer science, or a related field. 
• Six or more years of experience in data science, product analytics, or a related analytics role. 
• Two or more years of people management experience, including coaching, performance management, and team development. 
• Demonstrated ability to define metrics and measurement frameworks for product adoption, engagement, and value. 
• Proven ability to structure ambiguous problems and deliver clear analytical approaches and outputs. 
• Strong proficiency in SQL and Python for analysis, and experience with data visualization tools used for executive reporting. 
• Experience working with modern data warehouse or lakehouse technologies.
• Strong foundation in machine learning, statistical modeling, and data mining techniques. 
• Excellent communication and presentation skills, including ability to influence technical and non-technical senior stakeholders. 
• Demonstrated ability to manage competing priorities and deliver results in a fast-paced environment. 

Nice To Haves

• Master’s degree or PhD in a quantitative field. 
• Experience leading analytics for platform, infrastructure, or internal tooling products. 
• Familiarity with Agile delivery practices and common work management tools used to run sprints and track delivery. 
• Experience with analytics engineering or orchestration frameworks (for example, dbt or Airflow). 
• Working knowledge of software delivery lifecycle concepts and related operational metrics. 
• Familiarity with AI-assisted development tools used to support coding and delivery workflows. 
• Experience building or scaling an analytics team function, including defining standards and repeatable processes.

Responsibilities

• Lead, manage, and develop a team of data scientists and analysts through goal setting, coaching, feedback, and performance management.
• Define and own measurement frameworks that quantify adoption, engagement, feature effectiveness, and value delivery across internal developer platforms and tools.
• Partner with senior product and engineering leaders to align analytics priorities with developer productivity and technology efficiency objectives. 
• Analyze large, complex datasets (for example, pipeline events, activity logs, and usage telemetry) to identify trends and opportunities across the software development lifecycle. 
• Direct the development of models that quantify the impact of workflow automation and generative AI tools on delivery speed and engineering outcomes. J
• Guide experiment design and evaluation to test hypotheses on adoption, feature changes, and workflow improvements, ensuring results are methodologically sound.
• Oversee dashboards and recurring reporting that make key metrics easy to understand and actionable for leaders and teams.
• Drive scalable analytics engineering pipelines and dependable data flows from source systems to reporting and modeling layers. 
• Communicate analytical findings as clear, decision-ready recommendations for senior stakeholders across Product, Technology, and Finance. 
• Set standards for analytical rigor, documentation, and reusable assets, improving consistency across workstreams. 
• Stay current on product analytics and developer productivity measurement practices, bringing new approaches into the team’s work. 

Benefits

• We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location.
• Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. 
• We also offer a range of benefits and programs to meet employee needs, based on eligibility.
• These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more.
• Additional details about total compensation and benefits will be provided during the hiring process. 

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees