Capital One is looking to strengthen its risk management and Anti-Money Laundering (AML) programs by building out new Machine Learning and AI models to improve their List Screening models and expand innovation in other key areas within Compliance & Ethics.
Requirements
- Python
- SQL
- standard machine learning and modeling techniques
- generative AI
- open-source languages
- developing data science solutions using open-source tools and cloud computing platforms
- built models, validated them, and backtested them
- experience with clustering, classification, sentiment analysis, time series, and deep learning
- retrieve, combine, and analyze data from a variety of sources and structures
- Experience working with AWS
- At least 2 years’ experience in Python, Scala, or R
- At least 2 years’ experience with machine learning
- At least 2 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
- 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 data science solutions using open-source tools and cloud computing platforms.
Other
- managing complex projects to the highest levels of quality
- ability to communicate the vision to both technical and non-technical stakeholders
- strong sense of curiosity, who does not settle for the status quo
- Innovative
- Creative
- Statistically-minded
- A data guru
- 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 2 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
- Master’s Degree in “STEM” field (Science, Technology, Engineering, or Mathematics), or PhD in “STEM” field (Science, Technology, Engineering, or Mathematics)
