Senior Associate, Data Science
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. Team Description: The Credit Risk Management, Loss Forecasting and Allowance team uses the latest technologies and innovative models and data to forecast and optimize future losses associated with Capital One’s credit portfolio. We partner with model development and software engineering teams to build predictive models and automate insight generation. As a Data Scientist, you will focus on loss forecasting modernization and data transformation. The qualified candidate will support card loss forecasting: resilience, outlook, allowance and CCAR. Role Description In this role, you will: Partner with a cross-functional team of data scientists, software engineers, and product managers to identify and quantify risks associated with models Leverage a broad stack of technologies — Python, Conda, AWS, Spark, and more — to reveal the insights hidden within data Build statistical/machine learning models to challenge “champion models” that are deployed in production today Contribute to the model governance of the next generation of machine learning models Flex your interpersonal skills to present how model risks could impact the business to executives
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 2 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
Nice To Haves
- Master’s Degree in “STEM” field (Science, Technology, Engineering, or Mathematics), or PhD in “STEM” field (Science, Technology, Engineering, or Mathematics)
- Experience working with AWS
- At least 2 years’ experience in Python, Scala, or R
- At least 2 years’ experience with machine learning
- At least 2 years’ experience with SQL
Responsibilities
- Partner with a cross-functional team of data scientists, software engineers, and product managers to identify and quantify risks associated with models
- Leverage a broad stack of technologies — Python, Conda, AWS, Spark, and more — to reveal the insights hidden within data
- Build statistical/machine learning models to challenge “champion models” that are deployed in production today
- Contribute to the model governance of the next generation of machine learning models
- Flex your interpersonal skills to present how model risks could impact the business to executives
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
