Capital One is looking to solve the complex, multi-billion dollar problem of business data, which is poorly served by legacy providers, by building a market leading, business critical Business Data Product and Platform that gives customers a competitive advantage through information.
Requirements
- Strong background in ML/AI and engineering practices with experience in Entity Resolution, Information Retrieval, Graph-based ML, LLM/Embeddings or Deep Learning
- Experience with open-source languages and developing data science solutions using open-source tools, cloud computing platforms, and handling data at large scale using tools like pyspark
- Hands-on experience with clustering, classification, sentiment analysis, time series, and deep learning
- 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
Other
- Currently has, or is in the process of obtaining 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
- 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
- Must be willing to accept applications for a minimum of 5 business days
- Must be eligible to work in the US
- Must be willing to work in a team environment
