JPMorgan Quant Analytics Associate - Consumer Community 

United States, Delaware, Wilmington 

7134187

As a Quantitative Analytics Associate, in CCB Collections and Recovery, you will play a key role supporting data-driven decisions with direct impact to the financial bottom line collaborating with partners and stakeholders to drive operational excellence. You will leverage data governance, predictive analytics, strategy development, data science and machine learning disciplines to understand and predict customer and industry behavior, set quantifiable goals, identify opportunities and implement strategies through experimentation to enhance collections and recovery performance and effectively manage operational expenses for the organization.

Job Responsibilities

• Demonstrate robust data programming and analytical skills to efficiently collect, organize, analyze, and disseminate significant amounts of information with a high degree of attention to detail and accuracy.
• Monitor internal and external trends (customer/industry) and understand business drivers, underlying data and core operational processes to support strategic direction with independent and thoughtful insights.
• Leverage innovation, AI technology and design thinking to continually improve operational efficiency and resilience.
• Address issues with forward-looking solutions and collaborate across functions (Ops, Risk, Finance, Legal, Compliance, and Technology) to support design, testing and implementation of strategies to optimize return on investment and mitigate risks, amidst continuous change in an agile and demanding work environment.
• Interpret and present data clearly using narratives, visualizations, and context to convey insights and drive action.
• Become a subject matter expert and trusted partner to influence business direction and support operational success.

Required Qualifications, Capabilities, and Skills

• Beginner knowledge in statistics, finance, analytics, predictive modeling and machine learning techniques.
• Bachelor’s degree in Statistics, Economics, Econometrics, Operations Research, Mathematics, Finance or equivalent quantitative field, with 1+ year of applied analytical experience in complex and large data environments.
• Proven experience with programming languages (SQL, SAS, R, Python, Alteryx), relational databases (Oracle/Teradata), and visualization tools (Tableau) to effectively collect, analyze, uncover and communicate meaningful patterns and insights.
• Utilize logical reasoning and data analysis to solve problems and simplify complex techniques into actionable information using a variety of visual elements to inform and facilitate decision-making.
• Focus on results, continuous learning and process improvements to accelerate business objectives.
• Coordinate efforts and leverage diverse perspectives working effectively across functions to achieve common goals.
• Develop knowledge of products and services and understand roles within the business to support maximizing results.
• Proactively manage performance and work delivery expectations, set high-standards for self, act with sense of urgency and follow structured approach to manage multiple priorities and deliverables with high quality and error-free.
• Build and maintain positive relationships with clients and stakeholders, addressing their needs and interests effectively.
• Effective and clear communicator of risk-related issues, strategies and results with a variety of business partners.
• Positive culture carrier, curious and creative; collaborative, team-oriented, and client-focused; Willing to learn from experience, view challenges as opportunities, motivated by business and technical challenges and demonstrate openness to feedback for continuous improvement.

Preferred Qualifications, Capabilities, and Skills

• Master’s degree in relevant field.
• Previous applied risk and/or analytical experience in a financial services related industry.
• Applied Collections and Recovery knowledge/experience in Auto, Card, Retail and/or Business Banking product.

Monday through Friday, 8:00 am to 5:00 pm.

This is a Hybrid position, requiring the incumbent to commute/work on-site 3 days a week and work from home 2 days a week. Expected to become full in-office presence in Q1/Q2 2026