Job description

Join JPMorganChase's Business Banking division as a Data Scientist Director leading analytical team supporting a product vertical. This is a senior leadership role that requires strategic vision and depth in Data Science and AI/ML, the ability to translate between business strategy and technical execution, and a track record of building and managing high-performing analytics teams. You'll lead a group of analytics leaders, data scientists, and analysts responsible for delivering AI and analytics solutions that shape product strategy, customer experience, and competitive positioning across the Business Banking portfolio. The role spans three core areas: setting AI and analytical direction across product domains, serving as the bridge between senior business stakeholders and technical teams, and building organizational capability through talent development, inclusive culture, and operational excellence. Job Responsibilities • Define and drive the AI and analytics strategy for Business Banking D&A, identifying high-value opportunities for generative AI, agentic AI, and advanced analytics to create competitive advantage • Stay current on emerging AI/ML techniques and evaluate new capabilities, tools, and vendor offerings for practical application in the Business Banking business • Partner with Data, Product, Technology, Risk, and Finance to deliver Analytics and AI/ML solutions from ideation through production deployment, ensuring solutions are scalable, responsible, and aligned to business needs • Lead analytics supporting customer experience, product design, portfolio performance, and pricing and targeting strategies • Drive measurement frameworks, experimentation (including A/B testing and causal inference), and personalization strategies that improve customer experience and benefits utilization • Build and lead competitive intelligence capabilities that monitor market trends, competitor positioning, and industry benchmarks, partnering with external vendors and synthesizing internal and external data to give senior leaders a clear view of the competitive landscape • Deliver forward-looking analyses that inform strategic planning and product roadmap decisions • Serve as the connective tissue between business strategy and technical execution translating business problems into analytical frameworks and translating model outputs into executive-ready recommendations • Define analytical priorities with senior stakeholders, interpret results, and drive data-informed decisions across product, marketing, and servicing strategies • Lead, mentor, and develop a multi-layered team of analytics leaders, data scientists, and analysts, setting clear goals and performance expectations and providing ongoing coaching across all levels • Attract and retain top analytics talent through hiring, onboarding, and skills development programs • Champion a culture of innovation, intellectual rigor, inclusion, and collaborative problem-solving across the broader Business Banking D&A organization Required qualifications, capabilities, and skills • Bachlors Degree with 10+ years of progressive analytics experience • Senior leadership experience managing and developing multi-disciplinary analytics teams, including managers and individual contributors with strong coaching, org design, and talent development skills • Strong technical foundation in AI/ML, including experience evaluating and adopting emerging techniques, guiding architecture decisions, and moving solutions from prototype to production • Working knowledge of GenAI and agentic AI patterns, including large language models, retrieval-augmented generation, and agentic frameworks, with the ability to assess where they add value vs. simpler approaches • Exceptional ability to translate between technical and business audiences, with a track record of influencing senior leaders and cross-functional partners • Experience scoping and prioritizing a portfolio of analytical workstreams across multiple business domains in a large enterprise environment • Proficiency in Python and/or R, and experience with modern data platforms such as Snowflake or Databricks Preferred qualifications, capabilities, and skills • Experience in business banking, consumer lending, or payments analytics, including familiarity with lending and deposits products, credit risk, or customer lifecycle management • Experience building or leading competitive intelligence functions using alternative data, market data, or external benchmarking • Familiarity with data architecture concepts (ingestion, modeling, governance, quality) and MLOps/observability practices • Familiarity with responsible AI principles, model governance, and regulatory considerations in financial services • Experience enabling analytics adoption through change management, self-service tooling, or organizational enablement • Familiarity with Agile delivery methods and modern product practices Lead Data Science and AI/ML strategy for Business Banking products, building teams that deliver insight and impact.

Requirements

Must-haves

Define and drive the AI and analytics strategy for Business Banking D&A, identifying high-value opportunities for generative AI, agentic AI, and advanced analytics to create competitive advantage
Stay current on emerging AI/ML techniques and evaluate new capabilities, tools, and vendor offerings for practical application in the Business Banking business
Partner with Data, Product, Technology, Risk, and Finance to deliver Analytics and AI/ML solutions from ideation through production deployment, ensuring solutions are scalable, responsible, and aligned to business needs
Lead analytics supporting customer experience, product design, portfolio performance, and pricing and targeting strategies
Drive measurement frameworks, experimentation (including A/B testing and causal inference), and personalization strategies that improve customer experience and benefits utilization
Deliver forward-looking analyses that inform strategic planning and product roadmap decisions
Serve as the connective tissue between business strategy and technical execution translating business problems into analytical frameworks and translating model outputs into executive-ready recommendations
Define analytical priorities with senior stakeholders, interpret results, and drive data-informed decisions across product, marketing, and servicing strategies
Lead, mentor, and develop a multi-layered team of analytics leaders, data scientists, and analysts, setting clear goals and performance expectations and providing ongoing coaching across all levels
Attract and retain top analytics talent through hiring, onboarding, and skills development programs
Champion a culture of innovation, intellectual rigor, inclusion, and collaborative problem-solving across the broader Business Banking D&A organization
Required qualifications, capabilities, and skills
Bachlors Degree with 10+ years of progressive analytics experience
Senior leadership experience managing and developing multi-disciplinary analytics teams, including managers and individual contributors with strong coaching, org design, and talent development skills
Strong technical foundation in AI/ML, including experience evaluating and adopting emerging techniques, guiding architecture decisions, and moving solutions from prototype to production
Working knowledge of GenAI and agentic AI patterns, including large language models, retrieval-augmented generation, and agentic frameworks, with the ability to assess where they add value vs. simpler approaches
Exceptional ability to translate between technical and business audiences, with a track record of influencing senior leaders and cross-functional partners
Experience scoping and prioritizing a portfolio of analytical workstreams across multiple business domains in a large enterprise environment
Proficiency in Python and/or R, and experience with modern data platforms such as Snowflake or Databricks
Experience in business banking, consumer lending, or payments analytics, including familiarity with lending and deposits products, credit risk, or customer lifecycle management
Experience building or leading competitive intelligence functions using alternative data, market data, or external benchmarking
Familiarity with data architecture concepts (ingestion, modeling, governance, quality) and MLOps/observability practices
Familiarity with responsible AI principles, model governance, and regulatory considerations in financial services

Nice-to-haves

Preferred qualifications, capabilities, and skills

Application prep

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Keywords to mirror

aimlpythonagile

Platform: oracle-cloud
Effort: medium

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