Capital One is seeking to solve the problem of transaction fraud by developing and enhancing next-generation fraud detection models using machine learning and data science techniques.
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 1 year of experience working with AWS
- At least 3 years’ experience in Python, Scala, or R
- At least 3 years’ experience with machine learning
- At least 3 years’ experience with SQL
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
- Customer first. You love the process of analyzing and creating, but also share our passion to do the right thing.
- Innovative. You continually research and evaluate emerging technologies.
- 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
- Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
- Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 5 years of experience performing data analytics
