Senior Associate, Data Scientist
AI summary of the role
Data Scientist on Credit Risk Management team focusing on loss forecasting modernization for Capital One's credit card portfolio.
What you’ll do
- Partner with data scientists, engineers, product managers to identify model risks
- Build statistical/ML models to challenge production champion models
- Leverage Python, Conda, AWS, Spark for data insights
- Contribute to ML model governance
What you’ll bring
- Bachelor's in quantitative field + 2 years data analytics or Master's/MBA quantitative
- Experience building, validating, backtesting statistical models
- Hands-on with open-source languages and cloud platforms
- Skills to handle big data from varied sources
Technologies
Python · Conda · AWS · Spark · SQL · Scala · R · machine learning
Source and classification
Internal deployment & tooling · Evidence for this classification:
Senior Associate, Data Scientist 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
More from the job description
Senior Associate, Data Scientist 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 card 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 w [... source excerpt omitted ...] es — 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 The Ideal Candidate is: 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 lov [... source excerpt omitted ...] 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: 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, Mathemati
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