Data Scientist (Small Business Product) - Senior Associate

JPMorganChase is hiring a Senior Associate Data Scientist to join the Small Business Data Product Analytics team in New York, NY. In this onsite role, you will work closely with product and cross-functional partners to build scalable product analytics foundations, lead and trigger measurement capabilities, and experimentation frameworks that help drive measurable growth for small business clients.

What you’ll do

• Partner with product, design, strategy, risk, controls, and customer teams to deliver analytical support for Small Business product initiatives and decision-making.
• Use statistical methods, data analysis, and AI-assisted approaches to address challenges across product performance, client engagement, and growth outcomes.
• Own 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 lead and trigger capabilities that improve demand generation and client traffic in a scalable, sustainable way.
• Help establish day-one measurement, including tracking, data quality, and KPI frameworks spanning financial, operational, controls, audit, and product dimensions.
• Operationalize experimentation frameworks to evaluate product and journey enhancements, quantify impact, and support prioritization.
• Analyze client experience and journey outcomes, including AI-enabled discovery and servicing pathways, to identify opportunities for improvement and measurable value creation.
• Identify and build high-value AI and agentic use cases that improve analytical productivity, decision quality, and client outcomes.

What you bring

• 3-5 years of related analytics experience.
• Master’s or PhD in a related field, or a Bachelor’s with 3-5 years’ experience in a related discipline.
• Strong command of statistical analysis, text mining, hypothesis testing, predictive modeling, and experimental design for product and customer use cases.
• Experience using modern analytical tools and programming languages for data querying, transformation, and analysis, including Python and SQL.
• AI fluency, including the ability to use AI tools effectively in day-to-day analytical work to accelerate insight generation and improve solution quality.
• Experience with data visualization tools such as Tableau, Sigma, and Adobe Analytics.
• Ability to translate ambiguous business questions into structured analytical approaches and actionable recommendations.
• Strong data storytelling skills, including communicating complex concepts to audiences at different levels across business and technical teams.
• Proven ability to collaborate in cross-functional environments, align stakeholders, and deliver high-quality outputs in a dynamic product setting.
• Commitment to iterative development and measurable outcomes, including incorporating feedback and continuously improving analytical and AI-enabled solutions.
• Learning agility and curiosity to stay current on AI advances and apply them responsibly in a regulated environment.

Technologies

• Python
• SQL
• Tableau
• Sigma
• Adobe Analytics

Location and salary

• Location: New York, NY (onsite)
• Salary: USD 123,500 - 170,000 per year

Benefits

• Comprehensive health care coverage
• On-site health and wellness centers
• A retirement savings plan
• Backup childcare
• Tuition reimbursement
• Mental health support
• Financial coaching

Preferred qualifications

• Master’s degree in a related field.
• 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 for 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.