Manager, Data Science - Model Risk Office

Overview Data is at the center of everything we do. Capably our startup turned credit card offerings into personalized experiences through statistical modeling and relational database. Today we are a Fortune 200 company leading data‑driven decision making. As a Data Scientist you will be part of the Model Risk Office, responsible for validating payment network business models—including fraud risk, AML, counterparty risk and financial models—while working closely with business groups and stakeholders. Responsibilities Perform independent model validations for payment network models in accordance with regulatory guidance SR 11‑7 and internal model risk policy and standards. Validate fraud and AML modeling approaches, including rule‑based systems and thresholds, statistical models, and machine learning models (e.g., Gradient Boosting, Random Forest). Maintain the efficiency and accuracy of models through continuous improvement and best practices. Develop and maintain high‑quality documentation and transparently communicate risks and opportunities. Leverage open‑source technologies and tools to identify opportunities in our existing framework. Keep up‑to‑date with analytical technology and emerging tools. Understand business processes and model uses, and translate technical findings to non‑technical audiences and senior management. Ideal Candidate Customer‑first mindset and passion for doing the right thing. Innovative with a strong track record of researching and applying emerging technologies. Creative problem‑solver who asks questions and finds answers. Hands‑on experience in open‑source languages and cloud computing platforms. Statistically‑oriented, knowledgeable in confusion matrices, ROC curves, clustering, classification, sentiment analysis, time series and deep learning. A data guru comfortable with large data sets, data retrieval, and integration from multiple sources. Basic Qualifications Currently has or is in the process of obtaining one of the following with expected completion before start date: A Bachelor's degree in a quantitative field plus 6 years of data analytics experience. A Master’s degree in a quantitative field or an MBA with a quantitative concentration plus 4 years of data analytics experience. A PhD in a quantitative field 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 data analytics experience. At least 1 year of experience with AWS. At least 4 years of experience in Python, Scala, or R for large‑scale data analysis. At least 4 years of experience with machine learning. Salary and Incentives McLean, VA: $197,300 – $225,100 for Manager, Data Science. Riverwoods, IL: $179,400 – $204,700 for Manager, Data Science. Eligible for performance‑based incentive compensation, including cash bonus and/or long‑term incentives. Benefits Capital One offers a comprehensive, competitive, and inclusive set of health, financial, and other benefits that support your total well‑being. Eligibility varies by status and management level. Equal Opportunity Employer Capital One is an equal opportunity employer (EOE, including disability/veteran) committed to non‑discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug‑free workplace and considers qualified applicants with a criminal history in a manner consistent with applicable laws. #J-18808-Ljbffr National Science Teachers Association