Manager, Data Science, Model Risk Office
Capital One
McLean, VA1+ yrs2h agovia LinkedIn
This job at a glance
- Who can apply
- 1 year+ of experience · MBA / PGDM
- Must know
- Product managementSpark
- Nice to have
- StatisticsPythonAWSMachine learning
- Work
- On-site in McLean
- Pay
- Not stated by the employer.
- Skill demand
- Product management8%Statistics5%Python1%of 100 similar entry-level jobs posted in the US this week
- Listed
- Oct 31, 2026 · still open
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About the Role
The Model Risk Office defends the company against model failures and finds new ways of making better decisions with models. The Card Model Risk team specifically 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.
Key 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 interpersonal skills to translate the complexity of work into tangible business goals.
Requirements & Tech Stack
- Python
- Conda
- AWS
- H2O
- Spark
- Relational Databases
- Machine Learning
- Statistical Modeling
- Monitoring Tools
- Analytical Tools
Qualifications
Basic Qualifications
- 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.
- OR 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.
- OR 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 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.