Quant Analytics Associate - Card Data Anaytics

We're driven by curiosity, passion, optimism, and the belief that everybody can grow.

The Data Science Associate, Card Lending & Strategic Analytics, is a unique opportunity for a well‑rounded data analytics professional to leverage data science methods and analytics to deliver actionable customer insights and data-driven solutions across the Card business.

As a Data Science Associate within the Card Lending & Strategic Analytics team, you will leverage your skills in building analytics, analysis, data querying, and extracting customer 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, proficiency in SQL/Python programming, visualization methods, and technologies. You will have the opportunity to leverage your knowledge and analytical skills to uncover novel use cases of Big Data analytics that can be deployed at scale across the Credit Card business.

• Work with partners across Card Strategy and Lending to provide data insights and support portfolio strategies.
• Help partners in the Card business define their problems, understand root causes, and scope analytical solutions — uncovering novel, scalable use cases of Big Data analytics across the Credit Card business.
• Build an in-depth understanding of the Card domain and available data assets.
• Research, design, implement, and evaluate analytical approaches and models, including ad-hoc exploratory analyses and data mining across small-scale to "big data" datasets.
• Take initiative in evaluating and adapting new approaches from data science research.
• Investigate data visualization and summarization techniques, and communicate findings and obstacles to stakeholders to drive delivery to market.
• Code your solutions (this is a hands-on position requiring exceptional programming skills).
• Leverage AI agents and LLM-based tools to streamline analyses and automate the generation of insights, documentation, and reporting narratives.
• Collaborate across teams to deliver the best solution for the client, working with a wide range of internal resources.

• Bachelor's degree in relevant quantitative field required.
• 2+ years of hands‑on experience with data analytics; experience evaluating complex business problems, data analysis and devising recommendations and analytics to solve those business problems.
• Exceptional analytical, quantitative, problem solving, and communication skills.
• Excellent leadership, consultative partnering and collaboration across teams.
• Knowledge of statistical software and modern analytics tools (e.g., Python, R, SAS, SQL, Hive, Hadoop, Spark, Tableau, Alteryx).
• Ability to convey complex information in an understandable, compelling, and persuasive manner to both technical and non-technical audiences.

• Advanced degree preferred in analytical field (e.g. Statistics, Economics, Applied Math, Operations Research, other Data Science fields)
• Understanding of the key drivers within the credit card P&L is preferred.
• Financial services background preferred, but not required.