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# Senior Associate, Data Scientist - Operational Risk Management

- **Company:** Capital One Financial Corporation
- **Location:** Richmond, VA, United States
- **Experience:** Expert
- **Salary:** $135,600.0 - $154,800.0
- **Contract:** Permanent contract
- **Skills:** Amazon Web Services, Data Analysis, Big Data, Python (Programming Language), Machine Learning, Open Source Technology, Sentiment Analysis, SQL Databases, Cloud Platform System, Apache Spark, Deep Learning, Generative AI, Information Technology, Data Analytics
- **Published:** August 8, 2026
- **Apply:** https://dejobs.org/x/x/5CF311F3655A4F8E8C8BDEFEC069B9BF/job/

## About the Role

* 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 love asking questions and pushing hard to find answers. You're not afraid to share a new idea.
 * Technical. You're comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing data science solutions using open-source tools and cloud computing platforms.
 * 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.
 * A data guru. "Big data" doesn't faze you. 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., * 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, * 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 of experience in Python, Scala, or R
 * At least 2 years of experience with machine learning
 * At least 2 years of experience with SQL

## Description

The Operational Risk Analytics, Innovation, and Reporting team owns and drives end-to-end data analysis and reporting of Capital One's operational risk performance, delivering critical insights to Senior Executives and the Board. The team is responsible for the governance, monitoring, and analysis of operational risk data, as well as developing data-driven insights to inform strategic risk management decisions and practices. As a Senior Data Scientist you'll be part of a team that's leading the next wave of disruption in risk data at a whole new scale. You will use the latest in computing and machine learning technologies to unlock the big opportunities that help drive efficiency and improve risk management, and you will do it all in a collaborative environment that values your insight, encourages you to take on new responsibility, promotes continuous learning, and rewards innovation. You will be the driving force to experiment, innovate, and create next-generation features powered by
the latest emerging NLP and Generative AI technologies. If you love a fast-paced, highly rewarding environment, and you love being a builder and communicator, this is the place for you.

In this role, you will:

 * 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


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