Capital One is looking to solve complex problems in data-driven decision-making, specifically in the Commercial Bank Team with a $100B+ loan portfolio, by leveraging machine learning technologies and analytical tools to forecast bank loss on emerging risks.
Requirements
- Hands-on experience developing data science solutions using open-source tools and cloud computing platforms
- Experience with clustering, classification, sentiment analysis, time series, and deep learning
- 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
- Experience with big data and ability to retrieve, combine, and analyze data from a variety of sources and structures
Responsibilities
- 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
Other
- Currently has, or is in the process of obtaining 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
- 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
- Capital One will consider sponsoring a new qualified applicant for employment authorization for this position
- Travel requirements not specified
- Must be willing to work in a team environment and collaborate with cross-functional teams
