Data Science Manager

Capital One

full-time

Posted on: 9/25/2025

Origin: • 🇺🇸 United States • New York, Virginia

✨ AI Apply

💰 $193,400 - $240,800 per year

Junior

AWSCloudOpen SourcePythonScalaSparkSQL

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 insights within large volumes of numeric and textual data.
Build machine learning and generative AI solutions through all phases: design, training, evaluation, validation, and implementation.
Mine for real time insights hidden in large internal and external datasets to inform business decisions.
Translate complex technical work into tangible business goals and communicate results to stakeholders.
Focus on experimentation, predictive modeling, and generative AI applied to Commercial Banking use cases.

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: Bachelor's Degree in a quantitative field plus 6 years of experience performing data analytics; OR Master's Degree in a quantitative field or MBA with quantitative concentration plus 4 years of experience performing data analytics; OR PhD in a quantitative field plus 1 year of experience performing data analytics.
At least 1 year of experience leveraging open source programming languages for large scale data analysis.
At least 1 year of experience working with machine learning.
At least 1 year of experience utilizing relational databases.
Preferred: PhD in STEM plus 3 years of experience in data science / AI in Finance or Banking.
Preferred: At least 1 year of experience working with AWS.
Preferred: At least 4 years’ experience in Python, Scala, or R for large scale data analysis.
Preferred: At least 4 years’ experience with machine learning.
Preferred: At least 4 years’ experience with SQL.
Hands-on experience developing data science solutions using open-source tools and cloud computing platforms.
Experience with clustering, classification, sentiment analysis, time series, and deep learning.
Prior experience applying AI/ML in finance from a professional background is desirable.
Comfortable with open-source languages and passionate about developing further.