Data Scientist Director – Business Banking Client Analytics

Bring your expertise to JPMorganChase and help shape how we serve small business clients through data-driven strategy. You will lead a high-performing organization and turn advanced analytics into measurable business outcomes, influencing senior leaders and accelerating innovation.

As a Data Scientist Director at JPMorganChase within the Business Banking Client Analytics team, you will set the analytics vision and lead end-to-end delivery of solutions that support business growth, customer engagement, and market expansion. You will synthesize internal and external data to clarify the competitive landscape and inform executive decision-making. You will also develop and inspire leaders across data science and analytics, building an inclusive culture that values intellectual rigor, continuous improvement, and practical impact.

Job responsibilities

• Lead and develop a team of analytics leaders, data scientists, and analysts delivering advanced analytics and strategic insights for business banking strategy
• Define and execute customer segmentation and targeting frameworks to identify and size growth opportunities
• Build measurement and experimentation capabilities, including test-and-learn and causal approaches, to quantify impact and optimize outcomes
• Translate client, product, and transaction data into actionable insights that inform marketing, product, and servicing strategies
• Develop competitive intelligence analytics that monitor market trends, competitor positioning, and relevant industry benchmarks
• Synthesize internal and external data sources (including vendor partnerships) to provide senior leaders a clear view of the competitive landscape
• Partner closely with Strategy, Finance, Risk Management, Compliance, Internal Audit, Investor Relations, and Data Governance to ensure analytic integrity and effective controls
• Establish clear goals and performance expectations; coach, mentor, and support career development across all levels of the team
• Attract, hire, onboard, and retain top analytics talent while strengthening skills through ongoing development programs
• Champion innovation, continuous improvement, and adoption of analytics solutions across the broader organization

Required qualifications, capabilities, and skills

• Master’s degree or PhD in Statistics, Data Science, Computer Science, Operations Research, Applied Mathematics, Economics, or a related quantitative discipline
• 10+ years of relevant experience in analytics, data science, or applied quantitative research in financial services
• 5+ years of applied quantitative research or model development experience supporting business banking or commercial financial institutions
• Demonstrated experience leading and managing teams of data scientists, analytics professionals, or technical experts
• Proven ability to deliver analytics-driven recommendations to business stakeholders in a consulting or advisory capacity (internal or external)
• Strong communication and storytelling skills, including translating complex technical concepts into clear strategies and influencing senior stakeholders
• Strong analytical and problem-solving skills, with the ability to frame ambiguous business problems into structured analytic approaches
• Strong risk and control mindset, including sound judgment, attention to data integrity, and appropriate issue escalation

Preferred qualifications, capabilities, and skills

• Experience in retail banking, small business banking, or commercial banking
• Experience enabling analytics adoption through change management, self-service analytics, or organizational enablement
• Experience using modern artificial intelligence tools and platforms (for example, Microsoft Copilot or similar technologies)
• Proficiency in Python, R, and SQL, plus experience with modern data platforms (for example, Snowflake or Databricks)
• Deep knowledge of machine learning and advanced analytics methods, including supervised and unsupervised learning, predictive modeling, natural language processing, and experimentation frameworks