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# Data Science Vice President - Wealth Management

- **Company:** JPMorgan Chase & Co.
- **Location:** Columbus, OH, United States
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** A/B Testing, Big Data, Computer Programming, Python (Programming Language), Linear Regression, Logistic Regression, Machine Learning, SQL Databases, Information Technology, Feature Selection
- **Published:** October 3, 2026
- **Apply:** https://jpmc.fa.oraclecloud.com/hcmUI/CandidateExperience/en/sites/CX_1001/requisitions/preview/210790449

## About the Role

* Bachelor's degree in a STEM-related field
 * 5+ years of industry experience delivering advanced analytics or data science solutions in a business setting
 * 2+ years of people management experience, including coaching, performance management, and team development
 * Demonstrated experience leading teams to deliver analytics and machine learning solutions that improve measurable business outcomes
 * Demonstrated ability to translate ambiguous business questions into well-defined analytical problem statements and success metrics
 * Hands-on experience applying statistical and quantitative techniques (for example, linear regression, logistic regression, decision trees, regularization methods, and feature selection/diagnostics)
 * Proficiency in developing analyses using modern data tools and programming (for example, SQL and Python) and working with large datasets
 * Experience communicating complex analytical findings to senior stakeholders through clear recommendations and structured narratives
 * Demonstrated ability to select appropriately simple or advanced methods based on problem complexity and expected business value, * Experience supporting wealth management, investing, or self-directed investing businesses
 * Master's degree or PhD in a quantitative field (for example, statistics, computer science, economics, or applied mathematics)
 * Experience building and scaling experimentation programs (for example, A/B testing, causal measurement approaches, or quasi-experimental design)
 * Demonstrated continuous learning in data science and applied machine learning (for example, courses, conferences, or competitions)

## Description

* Partner with product, strategy, and operations teams to identify high-impact opportunities and define measurable outcomes
 * Lead end-to-end analytics delivery, including problem framing, measurement design, insight generation, and executive-ready storytelling
 * Build and scale machine learning solutions that improve client outcomes, product performance, and operational efficiency
 * Develop and refine modeling and trigger capabilities that improve operational processes in a sustainable, scalable way
 * Analyze client behavior across segments and products to identify drivers of engagement, outcomes, and portfolio allocation patterns
 * Design and operationalize experimentation and test-and-learn frameworks to quantify impact and inform prioritization
 * Evaluate client journeys and experience outcomes to identify improvement opportunities and value creation metrics
 * Identify and develop high-value artificial intelligence and agentic use cases that elevate analytical productivity and decision quality
 * Coach and develop team members through clear standards, feedback, performance management, and career growth support