Senior Manager, Data Science
Capital One
AWSOpen SourcePythonScalaSpark
Principal Associate, Data Science
Capital One
full-time
Posted on:
Origin: • 🇺🇸 United States • New York, Virginia
Visit company websiteSalary
💰 $158,600 - $197,400 per year
Job Level
JuniorMid-Level
Tech Stack
AWSCloudPythonScalaSparkSQL
About the role
- Partner with a cross-functional team of data scientists, software engineers, and product managers to deliver high impact AI infused transformations to the Commercial Bank
- Leverage a broad stack of technologies — Python, AWS, Spark, and more — to reveal the insights hidden within huge volumes of numeric and textual data
- Build machine learning and generative AI solutions through all phases of development, from design through training, evaluation, validation, and implementation
- Mine for real time insights hidden in large internal and external datasets to help Capital One and our customers make crucial business decisions
- Flex interpersonal skills to translate the complexity of your work into tangible business goals
- Work end to end from concept to production, heavily focused on experimentation, predictive modeling and generative AI
Requirements
- 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 plus 5 years of experience performing data analytics; A Master's Degree in a quantitative field or an MBA with a quantitative concentration plus 3 years of experience performing data analytics; A PhD in a quantitative field
- Master’s Degree in “STEM” field plus 3 years of experience in data analytics, or PhD in “STEM” field (preferred)
- At least 1 year of experience working with AWS (preferred)
- At least 3 years’ experience in Python, Scala, or R (preferred)
- At least 3 years’ experience with machine learning (preferred)
- At least 3 years’ experience with SQL (preferred)
- Hands-on experience developing data science solutions using open-source tools and cloud computing platforms (Python, AWS, Spark)
- Experience building, validating, and backtesting statistical/machine learning models
- Experience with clustering, classification, sentiment analysis, time series, and deep learning
- Prior experience applying AI/ML in finance (professional or academic) is a plus
- Ability to translate complex technical work into tangible business goals
- Must be able to obtain required degree on or before scheduled start date (if in process)
