Data Scientist Lead - Customer Analytics

JPMorgan Chase & Co.; Columbus (OH); On-site; USD 150,000 - 190,000; Full time

Job summary

JPMorgan Chase & Co. seeks a Data Scientist Lead to own the analytics agenda for the ACE Core Consumer Banking pillar. Define the roadmap, lead measurement and experimentation, and turn complex questions into actionable recommendations affecting strategy, product, marketing, pricing, and distribution.

You will mentor analytics talent, collaborate with cross-functional partners, and raise analytical rigor while presenting insights to senior leaders for strategic resource allocation.

Qualifications

• Master’s degree in a quantitative discipline or a BS with 6+ years in data science, statistics, math, engineering, economics, finance, or related field.
• 6+ years of experience using SQL, Python, R or similar tools to analyze large-scale data in modern data environments.
• Expertise in statistical analysis, experimental design, A/B testing, machine learning, and measurement frameworks.
• Ability to lead an end-to-end analytics agenda with roadmap definition, prioritization, stakeholder management, and business impact.
• Strong executive communication, visualization, and presentation skills with clear recommendations and storytelling.
• Ability to manage multiple high-impact projects in a fast-paced cross-functional environment with data integrity.

Responsibilities

• Own the analytics roadmap for the Core Consumer Banking pillar, including prioritization, sequencing, delivery, and business impact.
• Serve as the primary analytics partner to business, product, marketing, finance, technology, and distribution leaders.
• Translate ambiguous executive questions into structured analytical plans, clear recommendations, and decision-ready narratives.
• Lead analyses and experiments across growth, engagement, retention, migration, pricing, servicing, and segment strategy.
• Define measurement strategies, including test design, success metrics, monitoring frameworks, readout standards, and business implications.
• Develop executive-ready presentations and narratives that translate analysis into clear recommendations for senior leaders.
• Mentor team members and establish analytical standards for methodology, governance, data quality, and storytelling.

Skills

SQL

Python

R

Statistical analysis

AB testing

Machine learning

Experiment design

Stakeholder management

Data visualization

Executive communication

Education

Master’s degree in a quantitative discipline

Bachelor’s degree + 6+ years experience

Job description

Join the Affluent, Core, and Emerging (ACE) Analytics team as a Data Scientist Lead, where you will own the analytics agenda for a strategic Consumer Banking customer pillar. You will define the roadmap, lead high-impact measurement and experimentation, and translate customer and business questions into recommendations that influence strategy, product, marketing, pricing, and distribution decisions. This role requires strong technical judgment, executive communication, and the ability to lead cross-functional partners through ambiguity while mentoring analytics talent and driving a high standard of analytical rigor.

As a Data Scientist Lead on the ACE Analytics team, you will own the analytics agenda for the Core Consumer Banking customer pillar. You will define the roadmap, lead measurement and experimentation, and translate complex customer and business questions into clear recommendations that influence strategy, product, marketing, pricing, and distribution decisions. This role requires strong technical judgment, executive communication, and the ability to lead cross-functional partners through ambiguity while mentoring analytics talent and raising the standard of analytical rigor.

Job responsibilities

• Own the analytics roadmap for the Core Consumer Banking customer pillar, including prioritization, sequencing, delivery, and business impact

• Serve as the primary analytics partner to business, product, marketing, finance, technology, and distribution leaders

• Translate ambiguous executive questions into structured analytical plans, clear recommendations, and decision-ready narratives

• Lead analyses and experiments across growth, engagement, retention, migration, pricing, servicing, and segment strategy

• Define measurement strategies, including test design, success metrics, monitoring frameworks, readout standards, and business implications

• Develop executive-ready presentations and narratives that translate analysis into clear recommendations for senior leaders, influencing business strategy and resource allocation

• Mentor team members and establish analytical standards for methodology, governance, data quality, and storytelling

Required qualifications, capabilities, and skills

• Master’s degree in a quantitative discipline or Bachelor’s degree with 6+ years of experience in Data Science, Statistics, Mathematics, Engineering, Economics, Finance, or a related field

• 6+ years of experience using SQL, Python, R, or similar tools to analyze large-scale data in modern data environments

• Expertise in statistical analysis, experimental design, A/B testing, machine learning, and measurement frameworks

• Demonstrated ability to lead an end-to-end analytics agenda, including roadmap definition, prioritization, stakeholder management, and business impact

• Strong executive communication, visualization, and presentation-development skills, including experience translating analysis into clear recommendations and decision-ready storytelling

• Ability to manage multiple high-impact projects in a fast-paced, cross-functional environment while maintaining strong analytical rigor and data integrity

Preferred qualifications, capabilities, and skills

• Experience in financial services, consumer banking, customer strategy, or related industries

• Proven track record leading a book of work that delivers actionable insights and influences business strategy

• Collaborative leadership style with the ability to mentor talent and raise the standard of team output

• Knowledge of simulation, optimization, or advanced machine learning techniques