Capital One is looking to solve human capital problems, such as attracting, developing, and retaining top talent, ensuring a phenomenal associate experience, building a high performing and diverse executive pipeline, maximizing productivity, and rethinking how to measure talent.
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
- Experience with open-source languages
Responsibilities
- Designing and delivering modeling, as well as research and analysis in support of Capital One’s talent agenda
- Applying analytics to talent, combining machine learning and social science to build models that seek to understand associate behavior
- Informing strategies aimed at expanding Capital One’s talent advantage
- Leveraging structured problem solving approaches and data science skills to identify and deliver high impact solutions
- Developing unique data science skills and human-capital expertise
- Building models, validating them, and backtesting them
- Interpreting a confusion matrix or a ROC curve
Other
- Passionate about human capital
- Innovative and continually researching and evaluating emerging technologies
- Creative and able to bring definition to big, undefined problems
- Currently has, or is in the process of obtaining a Bachelor's Degree in a quantitative field plus 5 years of experience performing data analytics
- Ability to work in McLean, VA or other locations
