Job Responsibilities:

• Leverage your knowledge and analytical skills to help uncover novel use cases of Big Data analytics that can be deployed at scale across the ICB
• Help partners in the Marketing, Savings, Daily Banking, Operations define their business problems, understand root causes and scope analytical solutions to address it
• Research, design, implement, and evaluate analytical approaches and models
• Take initiative in evaluating and adapting new approaches from data science research
• Perform ad-hoc exploratory analyses and data mining tasks on diverse datasets from small scale to “big data”
• Investigate data visualization and summarization techniques for conveying key findings
• Communicate findings and obstacles to our stakeholders in the business to help drive the delivery to market
• Code your solutions (this is a hands-on position requiring strong programming skills)
• Collaborate across teams to deliver the best solution for client, working with a wide range of internal resources

Required qualifications, capabilities, and skills:

• Bachelor’s degree in relevant quantitative field required.
• Formal training or 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 packages (e.g. Python, R and SAS) and data querying languages (e.g. SQL).
• Experience across a broad range of modern analytics tools (e.g., SAS, SQL, Hive, Hadoop, Spark, Python, Tableau, Alteryx).
• Ability to convey complex information in an understandable, compelling, and persuasive manner to both technical and non-technical audiences.

Preferred qualifications, capabilities, and skills:

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