Join a team that designs and delivers analytical solutions that has measurable business impact through data?
As a Quant Analytics Manager, within the Collections Analytics team, you will design and deliver analytical solutions that has measurable business impact, spanning product benefit assessments, financial business cases, performance measurement, and strategy and channel optimization through data-driven insights and recommendations.
Job Responsibilities:
- Develop a deep understanding of the card, overdraft, and auto collections business — including product features, strategy, collections-specific performance metrics and terminology, and the nuances of collections data
- Conduct rigorous quantitative analysis using SAS, SQL, Alteryx, and/or Python to evaluate the performance of new and existing collections strategies and product features
- Identify opportunities to enhance existing strategies and product functionality; define and develop key performance indicators (KPIs) for new initiatives
- Build compelling financial business cases to support product initiatives and investment decisions
- Partner with Technology and Product teams to define data capture, storage requirements, and recommendations in support of future initiatives and platform migrations
- Champion analytical automation — identify and execute opportunities to streamline and scale analytical processes
- Serve as a strategic advisor to cross-functional partners, influencing stakeholders through clear, effective, data-driven storytelling
Required Qualifications, Capabilities & Skills:
- Bachelor's degree or higher in a quantitative discipline — Statistics, Mathematics, Data Science/Analytics, Engineering, Applied Economics, Management Information Systems, or equivalent; 7+ years of experience in an analytical, finance, or engineering-related role
- Demonstrated experience designing and interpreting A/B test analytics
- Proven track record in strategic analytics, business case development, and financial benefit sizing
- 7+ years of hands-on experience across a broad range of analytics technologies and tools including, SQL, Python, SAS, Alteryx, Snowflake, AWS, Tableau, Unix, and Excel, in a big data environment
- Experience leveraging Large Language Models (LLMs) and/or Agentic AI for analytical applications
- Self-starter with strong stakeholder management capabilities
- Comfortable operating in a dynamic, matrixed environment, managing multiple priorities under tight timelines
Preferred Qualifications, Capabilities & Skills:
- Foundational knowledge of credit card and retail businesses; collections-specific experience is a plus
- Background in risk, product, or marketing analytics