What are the responsibilities and job description for the Data Science Senior Associate - Card Data Analytics position at JPMorgan Chase?
You can help shape how data and AI drive decisions across our Credit Card business. You will work on high-impact problems end-to-end—translating business questions into analytical approaches, building models and solutions, and communicating insights that influence strategy and outcomes. Join a collaborative team where your work can directly improve customer and business experiences through responsible, scalable analytics.
As a Data Science Senior Associate at JPMorganChase within the Card Data & Analytics team, you will develop analytics and AI/ML solutions that support strategic initiatives and measurable business impact. You will partner across the Card organization to define problems, scope solutions, and deliver high-quality analytical products. You will combine consulting, data science, and programming to drive data science and analytics strategies and deliver actionable insights.
Job responsibilities
- Leverage experience and analytical skills to uncover novel use cases of Big Data analytics, including opportunities to responsibly apply foundation models and Generative AI
- Drive data science and analytics strategies, including recommendations on analytical products and standards
- Help partners define business problems and scope analytical solutions
- Build an understanding of problem domains and available data assets
- Research, design, implement, and evaluate analytical approaches and models, including Generative AI-based methods
- Perform exploratory statistics and data mining tasks on diverse datasets
- Communicate findings and obstacles to stakeholders to drive delivery to market
- Develop subject matter expertise in financial and operational domains
- Code solutions using strong programming skills
- Collaborate across teams to deliver the best solutions for clients
Required qualifications, capabilities and skills
- Formal training or certification on software engineering concepts and 3 years applied experience
- Bachelor’s degree in a relevant quantitative field and 3 years of data analytics experience, or advanced degree and 2 years of experience
- Exceptional analytical, quantitative, problem-solving, and communication skills
- Intellectual curiosity for solving business problems
- Leadership and collaboration skills
- Knowledge of statistical software (for example, Python, R, SAS) and data querying languages (for example, SQL)
- Familiarity with Generative AI and prompt engineering basics (prompt design, evaluation, guardrails)
- Experience with modern analytics tools (for example, SAS, SQL, Hive, Hadoop, Spark, Python, Tableau, Alteryx)
- Ability to convey complex information to technical and non-technical audiences
Preferred qualifications, capabilities and skills
- Experience with large language model-enabled applications such as retrieval-augmented generation, classification or extraction from unstructured text, or agent-like workflows; exposure to evaluation methods for quality, cost, and latency
- Understanding of key drivers within the credit card profit and loss statement
- Financial services background
- Master of Science degree or equivalent