Senior Manager, Data Science - Model Risk Office
About The Position
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. In Capital One’s Model Risk Office, we defend the company against model failures and find new ways of making better decisions with models. We use our machine learning, AI, software engineering, and business expertise to drive the best outcomes in both Model Risk Management and the Enterprise. The successful candidate will join the Card Model Risk team which is tasked with review and oversight of models used for underwriting Capital One’s flagship credit card products. You will use a variety of modeling, statistical, monitoring, and analytical tools to ensure models developed by data science practitioners across the company are effectively governed and lead to positive outcomes for the business.
Requirements
- 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: A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 7 years of experience performing data analytics
- A 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 5 years of experience performing data analytics
- A PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 2 years of experience performing data analytics
- At least 2 years of experience leveraging open source programming languages for large scale data analysis
- At least 2 years of experience working with machine learning
- At least 2 years of experience utilizing relational databases
Nice To Haves
- PhD in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 4 years of experience in data analytics
- At least 1 year of experience working with AWS
- At least 1 year of experience managing people
- At least 5 years’ experience in Python, Scala, or R for large scale data analysis
- At least 5 years’ experience with machine learning
Responsibilities
- 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
Benefits
- comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being
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What This Job Offers
Job Type
Full-time
Career Level
Senior
