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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Manager, Data Scientist - Recommendation & Personalization Systems - **Company:** Capital One Financial Corporation - **Location:** Richmond, VA, United States - **Salary:** $197,300.0 - $225,100.0 - **Contract:** Permanent contract - **Skills:** Amazon Web Services, Data Analysis, Big Data, Relational Databases, Python (Programming Language), Machine Learning, Open Source Technology, Standard Sql, Sentiment Analysis, Cloud Platform System, Deep Learning, Information Technology, Data Analytics - **Published:** October 3, 2026 - **Apply:** https://dejobs.org/x/x/EC8D57F2409E477D81753E45D5D31D48/job/ ## 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. * 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 6 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 4 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 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, * PhD in "STEM" field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics * At least 4 years of experience in Python, Scala, or R for large scale data analysis * At least 4 years of experience with machine learning * At least 4 years of experience with SQL * At least 1 year of experience working with AWS ## Description * 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. ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [How building an industry DBMS differs from building a research one](https://www.wearedevelopers.com/videos/768-how-building-an-industry-dbms-differs-from-building-a-research-one) - [How We Built a Machine Learning-Based Recommendation System (And Survived to Tell the Tale)](https://www.wearedevelopers.com/videos/752-how-we-built-a-machine-learning-based-recommendation-system-and-survived-to-tell-the-tale) - [The Innovation Formula: Fast Prototyping, Data Analysis, and Real User Insights](https://www.wearedevelopers.com/videos/1421-the-innovation-formula-fast-prototyping-data-analysis-and-real-user-insights) - [Why and when should we consider Stream Processing frameworks in our solutions](https://www.wearedevelopers.com/videos/1085-why-and-when-should-we-consider-stream-processing-frameworks-in-our-solutions) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Data Analyst Salary in the UK](https://www.wearedevelopers.com/magazine/278-data-analyst-salary-in-the-uk) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [What Industries Outside of AI Are Hiring The Most AI Experts?](https://www.wearedevelopers.com/magazine/98-what-industries-outside-of-ai-are-hiring-the-most-ai-experts)