As a Quantitative Analyst 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 cloud computing and machine learning technologies and operating across billions of customer records
Job Summary
As a Quantitative Analyst 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 cloud computing and machine learning technologies and operating across billions of customer records.
This position offers a unique opportunity to be a part of the modeling and quantitative analytics team in the dynamic Capital Markets & Analytics (CMA) organization at Capital One.
Our modelers thrive in a culture of mutual respect, excellence and innovation.
Matching Summary
As a Quantitative Analyst 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 cloud computing and machine learning technologies and operating across billions of customer records.
Salary
McLean, VA: $135,600 - $154,800; Bonus/Equity: performance based incentive compensation; Benefits: comprehensive, competitive, and inclusive set of health, financial and other benefits
Skills & Requirements
Must-have
quantitative modeling in finance
derivatives and fixed income models
Python or object-oriented language
cloud-based solutions
machine learning methods
model development process ownership
Nice-to-have
leading the next wave of disruption
culture of mutual respect, excellence and innovation
driving deeper market insights
making the complex simple
Key Requirements
Master's degree in quantitative field or MBA with quantitative concentration plus 1 year experience
1 year experience in statistical or econometric modeling
1 year experience in linear and logistic regression
1 year experience in programming in R, Python or SQL
1 year experience presenting statistical concepts to non-statistical audience
1 year experience in at least 3 of: Survival analysis, Time-series analysis, Panel data analysis, Cross-sectional data analysis, Machine learning, Analysis of large datasets (>1M records)