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.