Manager, Data Scientist - Card Intelligence Model Risk Management

Data is at the center of everything we do. As a startup, we disrupted the credit card industry by individually personalizing every credit card offer using statistical modeling and relational database technology back in 1988. Fast‑forward a few years, and this innovation and our passion for data has skyrocketed us to a Fortune 200 company and a leader in data‑driven decision‑making. Team Description The Card Intelligence Model Risk Management team sits in the Card Intelligence product organization, adjacent to Segments and Horizontal model development teams. The team drives our first line model risk management systemization agenda that aims to build out model development first line procedures, define model development methodology standards, collaborate with the second line Model Risk Office on central common component validation, and develop change management procedures to better manage ongoing systemic changes to data, platforms, and models. Role Description Partner with a cross‑functional team of data scientists, software engineers, and product managers to deliver a product customers love. Leverage a broad stack of technologies—Python, Conda, AWS, H2O, Spark, and more—to reveal the insights hidden within huge volumes of numeric and textual data. Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation. Translate the complexity of your work into tangible business goals and communicate them effectively. The Ideal Candidate Customer first. You love analysis and creation but also share a passion for doing the right thing for customers. Innovative. You research and evaluate emerging technologies, stay current on state‑of‑the‑art methods, and seek opportunities to apply them. Creative. You thrive on defining big, undefined problems, asking questions, and pushing to find answers. You’re not afraid to share new ideas. A leader. You challenge conventional thinking, work with stakeholders to improve the status quo, and are passionate about talent development for your team and beyond. Technical. You’re comfortable with open‑source languages and are eager to develop further, with hands‑on experience building data science solutions on open‑source tools and cloud platforms. Statistically‑minded. You’ve built models, validated them, and back‑tested them, and you know how to interpret confusion matrices, ROC curves, clustering, classification, sentiment analysis, time series, and deep learning. A data guru. “Big data” doesn’t faze you—you can retrieve, combine, and analyze data from a variety of sources and structures, understanding that data is often key to great data science. Basic Qualifications Currently has, or is in the process of obtaining, one of the following with the degree completed on or before the scheduled start date: Bachelor’s Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or related) plus 6 years of data analytics experience. Master’s Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or related) or an MBA with a quantitative concentration plus 4 years of data analytics experience. PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or related) plus 1 year of data analytics experience. At least 1 year of experience leveraging open‑source programming languages for large‑scale data analysis. At least 1 year of experience working with machine learning. At least 1 year of experience utilizing relational databases. Preferred Qualifications PhD in a STEM field plus 3 years of experience in data analytics. At least 1 year of experience working with AWS. At least 3 years’ experience leading model governance and end‑to‑end model development. At least 4 years’ experience in Python, Scala, or R for large‑scale data analysis. At least 4 years’ experience with machine learning. At least 4 years’ experience with SQL. Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. Salary Chicago, IL: $179,400 – $204,700 McLean, VA: $197,300 – $225,100 New York, NY: $215,200 – $245,600 Richmond, VA: $179,400 – $204,700 Other locations: subject to the associated pay range. Benefits Eligible for performance‑based incentive compensation, which may include cash bonus(es) and/or long‑term incentives. Comprehensive, competitive, and inclusive health, financial and other benefits that support total well‑being. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non‑discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug‑free workplace. #J-18808-Ljbffr Capital One