Job Description

We have an exciting opportunity for you to leverage data science methods to deliver actionable insights across the Card business.


As a Data Science Associate within the Card Data and Analytics team, you will leverage skills in building insights from advanced analytics, Gen AI / LLM tools, analysis, data querying, and extracting insights from big data to support our Credit Card business. This role is a hands-on mix of consulting know-how, analytical proficiency in statistics, data science, and machine learning/AI, proficiency in SQL/Python programming, visualization methods, and technologies.

Job Responsibilities:

Leverage your knowledge and analytical skills to uncover novel use cases of Big Data analytics for the Credit Card business. Support development of data science / AIML use cases for the Card business. Help partners in the Card business define their business problems and scope analytical solutions. Build an in-depth understanding of the Card domain and available data assets. Research, design, implement, and evaluate analytical approaches and models. Perform ad-hoc exploratory analyses and data mining tasks on diverse datasets. Communicate findings and obstacles to stakeholders to drive delivery to market.

Required Qualifications, Capabilities, and Skills:

Bachelor's degree in a relevant quantitative field required in an analytical field (e.g., Statistics, Economics, Applied Math, Operations Research, other Data Science fields). 4+ years of hands-on experience with data analytics; experience evaluating complex business problems and devising recommendations. Exceptional analytical, quantitative, problem-solving, and communication skills. Excellent leadership, consultative partnering, and collaboration across teams. Knowledge of statistical software packages (e.g., Python) and data querying languages (e.g., SQL). Experience across a broad range of modern analytics tools (e.g., Snowflake, Databricks, SQL, Spark, Python).

Preferred Qualifications, Capabilities, and Skills:

Understanding of the key drivers within the credit card P&L is preferred. Financial services background preferred, but not required. * Master's degree or equivalent in an analytical field.