Data Science Senior Associate- Card Data & Analytics team

JPMorgan Chase & Co.; Wilmington (DE); On-site; USD 120,000 - 170,000; Full time

Job summary

JPMorgan Chase & Co. in Wilmington seeks a Data Science Senior Associate to develop AI/ML solutions for the Card Data & Analytics team.

You will collaborate with partners across the Card business to define problems, scope solutions, and deliver high-quality analytical models. This role blends consulting, data science, and programming to advance data science and analytics strategies, leveraging GenAI, big data, and modern tools.

Qualifications

• Bachelor’s degree in a relevant quantitative field with 3+ years of data analytics experience, or advanced degree with 2+ years.

Responsibilities

• Identify novel Big Data analytics use cases and responsibly apply GenAI.
• Define business problems with partners and scope analytical solutions.
• Develop understanding of problem domains and data assets.
• Design, implement, and evaluate analytical models including GenAI methods.
• Perform exploratory statistics and data mining on diverse datasets.
• Communicate findings to stakeholders to drive delivery to market.
• Develop subject matter expertise in financial and operational domains.
• Code solutions with strong programming skills.
• Collaborate across teams to deliver client-centric solutions.

Skills

Data analytics

GenAI basics

Python

R

SAS

SQL

Leadership

Collaboration

Problem solving

Communication

Education

Bachelor’s degree in quantitative field

MS degree or equivalent

Tools

SAS

Hive

Hadoop

Spark

Python

Tableau

Alteryx

Job description

As a Data Science Senior Associate in the Card Data & Analytics team, you will develop AI/ML solutions that drive the bottom line for our Credit Card business. You will utilize your skills in data analytics, consulting, and programming to support strategic initiatives and deliver actionable insights. Collaborate with partners across the Card business to define problems, scope solutions, and deliver high-quality analytical models. Your work will involve a mix of consulting, data science, and programming, with a focus on driving data science and analytics strategies.

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 GenAI-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 with strong programming skills.
• Collaborate across teams to deliver the best solutions for clients.

Required Qualifications, Capabilities, and Skills

• 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 (e.g., Python, R, SAS) and data querying languages (e.g., SQL).
• Familiarity with GenAI and prompt engineering basics (prompt design, evaluation, guardrails).
• Experience with modern analytics tools (e.g., 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 LLM-enabled applications such as retrieval-augmented generation, classification or extraction from unstructured text, or agent-like workflows; exposure to evaluation methods for LLM quality, cost, and latency.
• Understanding of key drivers within the credit card P&L.
• Financial services background preferred.
• M.S. degree or equivalent.