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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Director, Data Science (Remote-Eligible) - **Company:** Capital One Financial Corporation - **Location:** Frankfort, KY, United States - **Experience:** Expert - **Salary:** $286,200.0 - $326,700.0 - **Contract:** Permanent contract - **Skills:** Amazon Web Services, Data Analysis, Architectural Patterns, Big Data, Cloud Computing, Relational Databases, DevOps, Github, Python (Programming Language), Machine Learning, Open Source Technology, Ansible, Sentiment Analysis, Service-Oriented Architecture, SONAR (Symantec), Cloud Platform System, Deep Learning, Cloudformation, Information Technology, Data Analytics, Free and Open-Source Software, Api Design, Devsecops, Jenkins, Artifactory, Microservices - **Published:** July 24, 2026 - **Apply:** https://www.techcareers.com/job.asp?id=3331039226&tx=IT9386THI&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54 ## About the Role * A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. * 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., * 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 11 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 9 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 6 years of experience performing data analytics * At least 6 years of experience leveraging open source programming languages for large scale data analysis * At least 6 years of experience working with machine learning * At least 6 years of experience utilizing relational databases, * PhD in "STEM" field (Science, Technology, Engineering, or Mathematics) plus 5 years of experience in data analytics * At least 6 years of experience in Python, Scala, or R for large scale data analysis * At least 6 years of experience with machine learning * At least 2 year of experience working with AWS * At least 6 years of experience with complex architectural patterns (SOA), building APIs, microservices, and event streams * At least 6 years of experience with DevOps or DevSecOps and building CI/CD pipelines using Jenkins, Artifactory, Chef, Ansible, AWS CloudFormation templates, GitHub, and Sonar ## Description * Partner with a cross-functional team of software engineers, distinguished researchers, and solutions architects to drive great decisions through modeling * Define and drive towards an end state that is based on simplicity and the adoption of digital technologies, cloud hosting, and open source software. * Distill the details of complex interconnected modeling systems to influence senior business leaders on model strategy, business use, and risks * Assess, challenge, and at times defend state-of-the-art decision-making systems to internal and regulatory partners * Shape our practice of building machine learning models, from design through training, evaluation, validation, and implementation * Oversee development of benchmark and challenger models to stress test critical modeling decisions ## Related Videos - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [Innovating Developer Tools with AI: Insights from GitHub Next](https://www.wearedevelopers.com/videos/1268-innovating-developer-tools-with-ai-insights-from-github-next) - [Dev & Test in the Cloud? 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