Quant Analytics Associate- Regulatory Operations

Ready to transform data into impactful insights? Join us as a Quantitative Analytics Associate and make your mark with our dynamic team! Dive into data analysis, support diverse Lines of Businesses such as Auto Finance and Business Banking and drive strategic decision while advancing your career. With highly supportive leadership and programs to foster growth and career mobility, your skills and capabilities can increase and be fine-tuned to make you more agile and versatile in reaching your career potential.

• Collaborate with key stakeholders across the firm to understand case contexts and translate high-level requirements into detailed analytic steps.
• Query databases and manipulate data to identify correction populations, analyze financials, and create execution files using account, customer, and transaction-level data.
• Ensure accuracy in analytics by maintaining attention to detail and supporting the independent validation team with case requirements and code review.
• Automate repetitive analytics steps across cases using SAS macros and other relevant tools.
• Develop and apply analytics skills to deliver best-in-class solutions for customer issue treatment.

• Demonstrated ability to conduct data analysis with a focus on uncovering patterns and providing insightful reporting and capability to learn and work with tools such as SAS, SQL, Python, or R.
• Strong analytical and problem-solving skills with demonstrated ability to manage complex customer issues.
• Excellent attention to detail and commitment to accuracy.
• Ability to communicate complex findings clearly to both technical and non-technical stakeholders.
• Experience working in a fast-paced, deadline-driven environment and ability to work collaboratively across multiple teams and lines of business.
• High level of motivation and initiative and strong organizational and time management skills.
• Commitment to delivering exceptional customer service.

• Bachelor's degree in a quantitative discipline (Mathematics, Statistics, Physics, Engineering, Economics, Finance or related fields)
• Proficiency in data analysis tools and techniques (. , SAS, SQL, Python, R).