Manager, Data Science - Model Risk Office

Manager, Data Science - Model Risk Office 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 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. As a Data Scientist at Capital One, you’ll be part of a team that’s leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives. Capital One is selectively recruiting for a Manager for a Model Validation team. The individual would report to the Model Risk Office and work closely with the business groups. This position is responsible for validating payment network business models, including fraud risk, Anti‑Money Laundering (AML), Counterparty risk, and financial models. Strong communication skills are essential to effectively engage with a diverse group of stakeholders, irrespective of their technical background. Role Description Perform independent model validations for payment network models, including fraud, AML, counterparty and financial 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 Machine learning models (e.g., Gradient Boosting, Random Forest) Remain on the leading edge of analytical technology with a passion for the newest and most innovative tools. Understand relevant business processes and portfolios associated with model use. Understand technical issues in econometric, statistical, and machine learning modeling and apply these skills toward developing models and assessing model risks and opportunities. Communicate technical subject matter clearly and concisely to individuals from various backgrounds both verbally and through written communication; prepare presentations of complex technical concepts and research results to non‑specialist audiences and senior management. Maintain the efficiency and accuracy of our models through continuous improvement and application of best practices. Develop and maintain high quality and transparent documentation. Leverage the latest open‑source technologies and tools to identify areas of opportunity in our existing framework. The Ideal Candidate is: Customer first: loves the process of analyzing and creating, and shares our passion to do the right thing. Innovative: continually researches and evaluates emerging technologies, stays current on state‑of‑the‑art methods, and seeks opportunities to apply them. Creative: thrives on bringing definition to big, undefined problems and is not afraid to share new ideas. Technical: comfortable with open‑source languages, passionate about developing further, and has hands‑on experience developing data science solutions using open‑source tools and cloud computing platforms. Statistically‑minded: has built, validated, and backtested models, understands confusion matrices, ROC curves, and has experience with clustering, classification, sentiment analysis, time series, and deep learning. A data guru: “Big data” does not faze them; they can retrieve, combine, and analyze data from a variety of sources and structures, understanding that data is key to great data science. Basic Qualifications Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date: Bachelor’s Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 6 years of experience performing data analytics. Master’s Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration plus 4 years of experience performing data analytics. PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 1 year of experience performing data analytics. 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 (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics. At least 1 year of experience working with AWS. At least 4 years’ experience in Python, Scala, or R for large‑scale data analysis. At least 4 years’ experience with machine learning. Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full‑time annual salaries for this role are listed below, by location. McLean, VA: $197,300 - $225,100 Riverwoods, IL: $179,400 - $204,700 This role is also eligible to earn performance‑based incentive compensation, which may include cash bonus(es) and/or long‑term incentives (LTI). Incentives could be discretionary or non‑discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well‑being. Eligibility varies based on full or part‑time status, exempt or non‑exempt status, and management level. 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. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including Article 23‑A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901‑4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. This role is expected to accept applications for a minimum of 5 business days. No agencies please. For technical support or questions about Capital One’s recruiting process, please send an email to View email address on click.appcast.io. Capital One does not provide, endorse nor guarantee and is not liable for third‑party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe, and any position posted in the Philippines is for Capital One Philippines Service Corp. #J-18808-Ljbffr Hobbsnews