Data Scientist Lead-Vice President

JPMorgan Chase & Co.•Jacksonville, FL

3h•$147,250 - $215,000

About The Position

Are you passionate about applying data science and AI to optimize process engineering and shape client experiences at scale? If you enjoy solving complex business problems analytically, using AI in your day-to-day workflow, and influencing strategy for a critical line of business, then this opportunity is for you. As a Data Scientist for Operations on our Home Lending Data and Analytics team, you'll have the opportunity to be at the forefront of building a best-in-class, automated, digital-led Home Lending business, focused on deepening relationships with our more than 70 million Chase households. You'll need to partner cross-functionally to establish product analytics foundations, develop scalable machine learning and trigger-driven capabilities, and support testing and experimentation to improve measurable outcomes. You will incorporate AI-native thinking, including practical application of AI in everyday analysis, decision support, and innovation, as well as a strong curiosity to identify, prototype, and scale new agentic use cases that improve product and client outcomes. You'll need to be an avid learner with a growth mindset that's eager to apply data science and AI to help launch and evolve the top prioritized automation and customer relationship opportunities in Home Lending.

Requirements

Bachelor’s degree in quantitative field (Computer Science, Engineering, Operations Research, Statistics, Economics, Math, Physics or related discipline) and 5 years of experience in advanced analytics roles
Strong proficiency in statistical analysis, hypothesis testing, predictive modeling, and experimental design for product and customer use cases
Talented in data querying, transformation, and analysis using modern analytical tools and programming languages (Python and SQL)
Demonstrated AI fluency, including ability to use AI tools effectively in day-to-day analytical work to accelerate insight generation and improve solution quality
Competent leveraging data visualization tools such as Tableau
Experience translating ambiguous business questions into structured analytical approaches and actionable recommendations
Strong data storytelling capabilities, including communicating complex concepts to audiences of varying levels across business and technical functions
Demonstrated ability to work in cross-functional environments, align stakeholders, and deliver high-quality outputs in a dynamic product setting
Strong commitment to iterative development and measurable outcomes, with the ability to incorporate feedback and continuously improve analytical and AI-enabled solutions
Demonstrated learning agility and curiosity to stay current on AI advances and apply them responsibly in a regulated environment

Nice To Haves

Banking industry/product knowledge desired
Experience supporting product analytics, product launch measurement, and experimentation in client-facing businesses
Experience presenting analytical insights and recommendations to senior leaders and cross-functional decision-makers
Familiarity with analytics approaches such as customer journey optimization, lead management, and performance measurement frameworks
Experience developing, testing, or scaling AI-enabled and agentic use cases in business workflows
Experience partnering with product and technology teams to translate AI opportunities into practical, measurable outcomes

Responsibilities

Collaborate with product, strategy, and operations teams to provide analytical support for Home Lending Operations initiatives and decision-making
Apply statistical methods, data analysis, and AI-assisted approaches to solve business problems related to product performance, client engagement, and operational efficiency outcomes
Support end-to-end analytics delivery, from problem framing and measurement design through insight generation and communication to senior stakeholders
Develop and refine analytics approaches for machine learning and trigger capabilities that help improve the operations process in a scalable, sustainable manner
Partner cross-functionally to set up day-one measurements, including tracking, data quality, and KPI frameworks across operational and product dimensions.
Operationalize experimentation frameworks to evaluate product and operations enhancements, quantify impact, and inform prioritization.
Analyze client experience and journey outcomes, including AI-enabled discovery, to identify opportunities for improvement and measurable value creation
Identify and develop high-value AI and agentic use cases that can improve analytical productivity, decision quality, and customer outcomes