Manager, Data Scientist - Card Intelligence Model Risk Management

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 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 In this role, you will: 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 Flex your interpersonal skills to translate the complexity of your work into tangible business goals The Ideal Candidate is: Customer first. You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it’s about making the right decision for our customers. Innovative. You continually research and evaluate emerging technologies. You stay current on published state‑of‑the‑art methods, technologies, and applications and seek out opportunities to apply them. Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You’re not afraid to share a new idea. A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You’re passionate about talent development for your own team and beyond. Technical. You’re comfortable with open‑source languages and are passionate about developing further. You have hands‑on experience developing data science solutions using open‑source tools and cloud computing platforms. Statistically‑minded. You’ve built models, validated them, and backtested them. You know how to interpret a confusion matrix or a ROC curve. You have experience with clustering, classification, sentiment analysis, time series, and deep learning. A data guru. “Big data” doesn’t faze you. You have the skills to retrieve, combine, and analyze data from a variety of sources and structures. You know understanding the data is often the 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 “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 3 years’ experience in 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 and Compensation McLean, VA: $197,300 - $225,100 New York, NY: $215,200 - $245,600 Richmond, VA: $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. This role is expected to accept applications for a minimum of 5 business days. No agencies please. 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 qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at View phone number on click.appcast.io or via email at View email address on click.appcast.io. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to View email address on click.appcast.io. 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