Quant Analytics Senior associate - Card Data Analaytics

We're driven by curiosity, passion, optimism, and the belief that everybody can grow.
As a Quantitative Analytics Senior Associate at JPMorganChase within Card Data & Analytics, you will deliver high-impact quantitative insights that shape strategies across cobrand credit card partnerships — from acquisition and engagement to retention and rewards optimization. Your work will directly influence partnership strategies, cardholder value, and customer experience, with meaningful visibility to senior leadership. This is an opportunity to bring your analytical expertise to a collaborative, fast-paced team where your insights drive real business outcomes.
Job responsibilities
Execute quantitative analytics to drive credit card portfolio strategy and performance across key metrics including acquisition, activation, spend, retention, and attrition
Develop innovative analytical solutions and frameworks to address complex business challenges across cobrand partnership programs
Consult on experimental design and testing strategies in collaboration with partners and internal teams to validate and scale initiatives
Present findings and actionable recommendations clearly and compellingly to senior management and cross-functional stakeholders
Maintain rigorous data controls to ensure accuracy, integrity, and compliance across all analytical outputs
Apply advanced analytical tools and models — including generative AI and segmentation frameworks — to uncover actionable insights
Collaborate closely with marketing, product, and Data & Analytics teams to align analytical work with broader business priorities
Optimize rewards structures and cardholder value propositions to enhance customer loyalty and engagement
Prepare and deliver partner reporting and performance insights to support cobrand relationship management
Required qualifications, capabilities, and skills
Formal training or certification on analytics concepts and 3+ years applied experience
Bachelor's degree in a quantitative field (e.g., Statistics, Mathematics, Economics, Computer Science) or an advanced degree with relevant analytical experience
Proficiency in statistical programming languages including Python, R, or SAS, and data querying languages such as SQL
Experience with modern analytics and data tools including Hive, Hadoop, Spark, Tableau, or Alteryx
Exceptional analytical and quantitative problem-solving skills with the ability to translate complex data into clear, actionable insights
Strong communication skills with the ability to convey complex information to both technical and non-technical audiences
Demonstrated intellectual curiosity and a proactive approach to solving ambiguous business problems
Familiarity with generative AI concepts and prompt engineering fundamentals
Preferred qualifications, capabilities, and skills
3 or more years of experience in the credit card industry, with exposure to cobrand or partnership programs
Experience with customer segmentation, lifecycle analytics, or rewards optimization strategies
Familiarity with experimental design methodologies such as A/B testing or champion/challenger frameworks
Demonstrated ability to influence strategy through data storytelling and executive-level presentations