Senior Manager, Data Scientist
Job Description
Senior Manager, Data Scientist on Capital One's Generative AI Systems team within Card Data Science, onsite in New York, NY; salary USD 245,900 - 280,600 per year.
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, Kubernetes, 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
Requirements
- Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 7 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 plus 5 years of experience performing data analytics
- PhD 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
- At least 2 years of experience leveraging open source programming languages for large scale data analysis
- At least 2 years of experience working with machine learning
- At least 2 years of experience utilizing relational databases
Technologies
- Python
- Kubernetes
- AWS
- H2O
- Spark
Team Description
The Generative AI Systems (Genesis) team within Card Data Science builds state-of-the-art, generative AI-based solutions for dialogue, text summarization, reading comprehension, speech recognition, image and document processing, as well as time-series sequencing modeling. We partner with product, tech and design teams to deliver internal applications based on these solutions that drive efficiency in our business and data analytics teams, as well as customer-facing applications.