Capital One is looking to solve the problem of First Party Fraud by building machine learning models that enable exceptional customer experiences while protecting the Bank from fraudsters and minimizing operational overhead.
Requirements
- Experience with clustering, classification, sentiment analysis, time series, and deep learning
- At least 3 years’ experience in Python, Scala, or R with proficiency in the following Python libraries: Polars, DBT, Hydra, and MLFlow
- At least 3 years’ experience with machine learning, including experience deploying a model into a (complex) production environment, ideally having built reusable/modular components along the way
- At least 2 years’ experience working in Operations Research or related areas, with an ability to build and optimize the policies that turn model scores into customer-impacting decisions
- At least 1 year’s experience working with graphs and building GNNs
- At least 1 year’s experience developing and deploying with Kubeflow Pipelines (ideal) or other workflow orchestration tools
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 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)
- Customer first. You love the process of analyzing and creating, but also share our passion to do the right thing
- Creative. You thrive on bringing definition to big, undefined problems
