As a Quant Analytics Associate in the Card Data and Analytics Team, you'll focus on cross-channel and cross-product analytics and data visualization. You'll analyze customer data across card products, design dashboards using Tableau, and present insights to executive staff. This high-visibility role involves collaborating with senior leaders to contribute innovative ideas and actionable insights, supporting the growth of the Chase credit card business.
Job responsibilities
- Design, develop, and maintain customer dashboards for the CCB Card D&A group using Tableau.
- Analyze Tableau dashboard insights to identify actionable opportunities and monitor initiative effectiveness.
- Present data and insights in an executive, visualized format.
- Automate data preparation for dashboards using tools like Alteryx, Snowflake, SAS, and SQL.
- Identify growth opportunities and communicate recommendations to influence marketing strategies.
- Collaborate with cross-functional teams to deliver analyses and strategic roadmaps.
- Identify opportunities to improve marketing cost efficiency and drive sustainable growth.
Required qualifications, capabilities and skills
- Minimum 4 years of experience in data visualization and analytics, with strong knowledge of Tableau and Tableau Server.
- Proficient in analytical and statistical tools such as Alteryx, SAS, and SQL.
- Excellent communication skills for interacting with leadership and delivering insightful analyses.
- Skilled in translating metrics into insights and presenting trends in an executive format.
- Experienced in data automation and ETL tools like Alteryx.
- Proven ability to analyze large datasets and research data mining issues.
- Strong problem-solving skills, especially in fast-paced environments.
Preferred qualifications, capabilities and skills
- Bachelor's degree in a quantitative field; Master’s in STEM preferred.
- Experience with digital platforms and tools like Adobe Analytics is a plus.
- Understanding of key drivers within credit card P&L is preferred.
- Experience with big data technologies and machine learning is advantageous.