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.