Data Science Manager, Commercial Banking 1054 views

At Capital One, they’re building a leading information-based technology company. Still founder-led by Chairman and Chief Executive Officer Richard Fairbank, Capital One is on a mission to help their customers succeed by bringing ingenuity, simplicity, and humanity to banking. They measure their efforts by the success their customers enjoy and the advocacy they exhibit. They are succeeding because they are succeeding.

Guided by their shared values, they thrive in an environment where collaboration and openness are valued. They believe that innovation is powered by perspective and that teamwork and respect for each other lead to superior results. They elevate each other and obsess about doing the right thing. Their associates serve with humility and a deep respect for their responsibility in helping their customers achieve their goals and realize their dreams. Together, they are on a quest to change banking for good.

Data Science Manager, Commercial Banking

At Capital One, data is at the center of everything they do. When they launched as a startup they disrupted the credit card industry by individually personalizing every credit card offer using statistical modeling and the relational database, cutting edge technology in 1988! Fast-forward a few years, and this little innovation and their passion for data has skyrocketed them to a Fortune 200 company and a leader in the world of data-driven decision-making. Twenty-five years after Capital One was started it’s still led by its founder. Be ready to join a community of the smartest people you’ve ever met, who see the customer first, and want to use their data skills to make a difference.

As a Data Science Manager at Capital One, you’ll be part of a team that’s leading the next wave of disruption at a whole new scale, using the latest in distributed computing technologies and operating across billions and billions of customer transactions to unlock the big opportunities that help everyday people save money, time and agony in their financial lives.

On Any Given Day You’ll Be

• Using Big Data tools (Hadoop, Spark, H2O, AWS) to conduct the analysis of billions of customer transaction records
• Writing software to clean and investigate large, messy data sets of numerical and textual data
• Integrating with external data sources and APIs to discover interesting trends
• Building machine learning models from development through testing and validation to our 30+ million customers in production
• Designing rich data visualizations to communicate complex ideas to customers or company leaders
• Investigating the impact of new technologies on the future of digital banking and the financial world of tomorrow

The Ideal Candidate Will Be

• Curious. You ask why, you explore, you’re not afraid to blurt out your disruptive idea. You probably know Python, Scala, or R and you’re constantly exploring new open source tools.
• Wrangler. You know how to programmatically extract data from a database and an API, bring it through a transformation or two, and model it into human-readable form (ROC curve, map, d3 visualization, Tableau, etc.).
• Creative. Big, undefined problems and petabytes of data don’t frighten you. You’re used to working with abstract data, and you love discovering new narratives in unmined territories.

Basic Qualifications

• Bachelor’s Degree plus 6 years of experience in data analytics, or Master’s Degree plus 4 years of experience in data analytics, or PhD plus 2 years of experience in data analytics
• At least 3 years’ experience in open source programming languages for large scale data analysis
• At least 3 years’ experience with machine learning
• At least 3 years’ experience with relational databases
• At least 1 years’ experience managing high-functioning data science/data engineering teams

Preferred Qualifications

• PhD in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 2 years of experience in data analytics
• At least 1 year experience working with AWS
• At least 1 year experience managing people
• At least 5 years’ experience in Python, Scala, or R for large scale data analysis
• At least 5 years’ experience with machine learning
• At least 5 years’ experience with SQL

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.