Data Analyst Manager - Model Risk Office

Responsibilities

• Builds and deploys scalable artificial intelligence and machine learning models to automate existing model risk management process, reporting and controls
• Architect and deploy an interactive, conversational reporting chatbot powered by AI solutions
• Experiment with and develop advanced, multi-agent AI workflows designed to execute complex cognitive tasks.
• Optimize data integration across core systems into centralized infrastructure to create a highly accurate, audited "source of truth" for model risk metrics
• Drive current and future strategy by leveraging your analytical skills
• Assist with building and using models to test and validate data
• Work with vast amounts of data in new and evolving environments
• Be a part of growing and developing our brand in new and emerging markets
• Leverage analytics to create a customer experience above our peers
• Lead a team of talented junior analysts on an exciting professional journey while mentoring them and elevating their careers
• Be a part of the full life cycle of projects and see end results
• Collaborate across business units
• Work with top talent in a fast paced, entrepreneurial environment where analytics and good data are a top priority
• Experience real work life balance, with little travel involved
• On any given day you will be:
• Mining data to arrive at specific and crucial information for the organization
• Identifying and implementing process, data, and reporting improvements for the organization
• Working with large and complex databases containing millions to billions of records
• Improving operational efficiencies and effectiveness
• Conducting analysis to evaluate processes and tests
• Extracting and analyzing data to gauge product offerings
• Consulting on the design and implementation of new production and data storage systems
• Developing and implementing strategic tests of products, initiatives and marketing materials

Requirements

• Currently has, or is in the process of obtaining a:
• Bachelor's Degree in quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science or a related quantitative field) plus at least 6 years of experience performing data analytics, or
• Master's Degree plus at least 4 years of experience performing data analytics with an expectation that required degree will be obtained on or before the scheduled start date.
• At least 4 years of experience performing professional data analysis work
• At least 4 years of experience performing programming
• Master's Degree in a Science, Technology, Engineering, Mathematics discipline
• At least 7 years of professional data analysis work experience
• At least 4 years of experience with Python, R, Spark or SQL
• At least 1 year of experience in people management
• At least 1 years of project management experience
• At least 1 year of experience in interactive reporting tools such as Tableau or Quicksight
• At least 1 years of experience in a Model Risk Management, Risk Governance, or highly regulated financial

Benefits

Additional Information

Data Analyst Manager - Model Risk Office At Capital One, data is at the center of everything we do. When we launched as a startup we disrupted the credit card industry by individually personalizing every credit card offer using statistical modeling and the relational database, cutting edge technology in 1988! Fast-forward a few years, and this little innovation and our passion for data has skyrocketed us to a Fortune 200 company and a leader in the world of data-driven decision-making. The Model Risk Governance - Reporting and Automation team sits within the Model Risk Office and serves for providing risk reporting to enterprise and process optimization for the department. Responsible for managing the enterprise-wide model risk reporting function, the team is actively driving a strategic transformation to replace legacy reporting with an interactive, GenAI-centric reporting ecosystem. In addition to innovating the reporting function, the team is deploying scalable, cutting-edge AI solutions-including intelligent multi-agent architectures-to eliminate repetitive manual workflows, optimize operational efficiency, and minimize human error. To accelerate this vision, the team has a vital need for forward-thinking talent eager to execute high-impact, AI-powered automation work that transforms how the enterprise visualizes and manages model risk.

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