In Capital One's Model Risk Office, we defend the company against model failures and find new ways of making better decisions with models. We use our statistics, software engineering, and business expertise to drive the best outcomes in both Risk Management and the Enterprise.
Requirements
- At least 3 years’ experience in Python, Scala or R. Experience with PySpark is a plus.
- At least 3 years’ experience with SQL
- At least 3 years’ experience with hands-on Machine Learning model development and deployment
- At least 1 years’ experience with AWS or other cloud computing platform
- Experience with model development/deployment pipeline (e.g. Kubeflow) is preferred.
- Experience with clustering, classification, sentiment analysis, time series, and deep learning.
Responsibilities
- 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
- Continually research and evaluate emerging technologies.
- Stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them.
- Develop further in open-source languages.
- Develop data science solutions using open-source tools and cloud computing platforms.
- Build models, validate them, and backtest them.
Other
- Partner with a cross-functional team of data scientists, software engineers, and product managers to deliver a product customers love
- Flex your interpersonal skills to translate the complexity of your work into tangible business goals
- 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 5 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 3 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)
