Location: New York, NY, United States

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

• Masters 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

Lead data science teams to deliver advanced analytics that drive growth, engagement, and competitive insight for small businesses.