Data Science Vice President - Card Data Analytics

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 AIDrive 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 Generative AI-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 using strong programming skills.
• Collaborate across teams to deliver the best solutions for clients.

Required Qualifications, Capabilities And Skills

• Formal training or certification on software engineering concepts and 5+ years applied experience.
• Bachelor's degree in a relevant quantitative field and 5+ 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 (for example, Python, R, SAS) and data querying languages (for example, SQL).
• Familiarity with Generative AI and prompt engineering basics (prompt design, evaluation, guardrails).
• Experience with modern analytics tools (for example, 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 large language model-enabled applications such as retrieval-augmented generation, classification or extraction from unstructured text, or agent-like workflows; exposure to evaluation methods for quality, cost, and latency.
• Understanding of key drivers within the credit card profit and loss statement.
• Financial services background.
• Master of Science degree or equivalent.