Data Science Senior Associate - Marketing Analytics

Job Description

You will join a collaborative team that applies advanced modeling, machine learning, and applied AI to profile clients across all lines of business, improve customer experience, and enable business performance at scale. You will take on the toughest analytical challenges the team faces-from customer segmentation to digital marketing to AI-enabled and agentic alert systems-and turn them around with speed and rigor. You will work on high-visibility initiatives, partner closely with business and technology teams, and help move ideas from concept into implemented solutions embedded in day-to-day workflows. You will also have opportunities to grow through mentoring, training, and mobility.

As a Data Scientist Associate Senior at JPMorganChase within the Consumer & Community Banking Data and Analytics organization, you will operate as a senior technical contributor and force-multiplier for the team. You will independently own end-to-end modeling solutions-framing ambiguous problems, building and validating models, and driving them into production-while helping set technical direction and elevating the work of others. You will ensure solutions are statistically sound, aligned to business objectives, delivered quickly, and integrated into business processes to drive adoption and measurable impact.

Job responsibilities

• Own the team's highest-priority modeling problems end to end, framing ambiguous questions and delivering rigorous solutions on tight timelines
• Design, build, validate, and deploy advanced models spanning customer segmentation, digital marketing, and AI-enabled and agentic alert systems
• Translate business objectives into well-scoped modeling problems with clear success criteria and measurable outcomes
• Apply machine learning, statistical, and mathematical methods to develop novel solutions-including unsupervised methods such as PCA and k-means, supervised methods such as regression, tree-based models, and gradient-boosted algorithms, as well as causal inference, forecasting, and simulations
• Build applied AI and agentic solutions, including large language model-based systems, prompt engineering, and developer and AI assistants
• Serve as a technical lead on complex workstreams, helping direct and prioritize team efforts and unblocking others
• Communicate results, insights, and recommendations clearly to business stakeholders, technology partners, and senior leadership
• Partner with data science, engineering, product, and design teams to ensure solutions are feasible, scalable, and production-ready
• Mentor and guide teammates on modeling approaches, code quality, and analytical rigor
• Manage multiple engagements by prioritizing work, tracking dependencies, and escalating risks and tradeoffs proactively

Required qualifications, capabilities, and skills

• Formal training or certification on data science concepts and 3+ years applied experience
• Undergraduate degree in a quantitative discipline or equivalent practical experience
• Strong programming skills in Python, including the modern data science and machine learning ecosystem
• Deep machine learning expertise across the full model lifecycle-feature engineering, training, validation, deployment, and monitoring
• Strong statistical and mathematical foundation, with the ability to select and apply the right technique to novel and ambiguous problems
• Applied AI engineering experience, including building large language model-based and/or agentic solutions and prompt engineering
• Proficiency with SQL and data querying at scale
• Demonstrated ownership mindset and ability to operate independently in ambiguous, fast-moving problem spaces
• Strong written, verbal, and presentation skills, with experience communicating effectively with both business and technology audiences, including senior leadership
• Ability to guide, mentor, and influence teammates and cross-functional partners

Preferred qualifications, capabilities, and skills

• Graduate degree (Master's or PhD) in a quantitative discipline
• Experience in financial services or retail banking
• Experience with modern data platforms such as Snowflake or Databricks
• Experience productionizing models and integrating them into business workflows
• Familiarity with experimentation, model lifecycle management, and machine learning operations practices

About Us

Chase is a leading financial services firm, helping nearly half of America's households and small businesses achieve their financial goals through a broad range of financial products. Our mission is to create engaged, lifelong relationships and put our customers at the heart of everything we do. We also help small businesses, nonprofits and cities grow, delivering solutions to solve all their financial needs.

We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.

We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.

Equal Opportunity Employer/Disability/Veterans

About the Team

Our Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We're proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions - all while ranking first in customer satisfaction.

The CCB Data & Analytics team responsibly leverages data across Chase to build competitive advantages for the businesses while providing value and protection for customers. The team encompasses a variety of disciplines from data governance and strategy to reporting, data science and machine learning. We have a strong partnership with Technology, which provides cutting edge data and analytics infrastructure. The team powers Chase with insights to create the best customer and business outcomes.