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# Senior Manager, Data Science - Model Risk

- **Company:** Capital One Financial Corporation
- **Location:** York, NY, United States
- **Experience:** Expert
- **Salary:** $229,900.0 - $262,400.0
- **Contract:** Permanent contract
- **Skills:** Amazon Web Services, Data Analysis, Big Data, Relational Databases, Python (Programming Language), Machine Learning, Open Source Technology, Sentiment Analysis, Software Engineering, Apache Spark, Deep Learning, Model Validation, Information Technology, Data Analytics
- **Published:** November 4, 2026
- **Apply:** https://www.capitalonecareers.com/job/mclean/senior-manager-data-science-model-risk/1732/102826235808

## About the Role

* A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You're passionate about talent development for your own team and beyond.
 * Customer first. You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it's about making the right decision for our customers.
 * 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.
 * Statistically-minded. You've built models, validated them, and backtested them. You know how to interpret a confusion matrix or a ROC curve. You have experience with clustering, classification, sentiment analysis, time series, and deep learning., * 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, * 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

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.

The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.

## Description

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 statistics, software engineering, and business expertise to drive the best outcomes in both Risk Management and the Enterprise. We understand that we can't prepare for tomorrow by focusing on today, so we invest in the future: investing in new skills, building better tools, and maintaining a network of trusted partners. We learn from past mistakes, and develop increasingly powerful techniques to avoid their repetition., * 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