Senior Manager, Data Science - AI Software Engineering
Role details
Job location
Tech stack
Job description
The AI Foundations - AI Software Engineering Data Science team designs, builds, and delivers state-of-the-art, scalable AI architectures that transform how software is developed at Capital One. We partner closely with product and engineering teams to create multi-agent solutions across the software development lifecycle-including code generation, migration, troubleshooting, root-cause analysis, and documentation-leveraging technologies such as LangGraph, MCP, agent-to-agent protocols, and advanced model customization techniques., * 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
Requirements
- 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 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