Manager, Data Science

114 5th Ave (22114), United States of America, New York, New York

At Capital One, we'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 our customers succeed by bringing ingenuity, simplicity, and humanity to banking. We measure our efforts by the success our customers enjoy and the advocacy they exhibit. We are succeeding because they are succeeding.

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

Manager, Data Science

At Capital One, data is at the center of everything we do. When we launched as a startup we 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 our passion for data has skyrocketed us to a Fortune 200 company and a leader in the world of data-driven decision-making.

As a Data Scientist 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:

- Working within a cross-functional team of data scientists, software engineers, and product managers to deliver a product customers love

- Owning a broad stack of technologies - Python, conda, AWS, and CI/CD frameworks - to translate customer needs large and small into tangible features

- Learning first-hand about the sophisticated suite of machine learning models which form the foundation of Capital One's business

- Having a transformative impact on the deployment of new modeling techniques and their path to deliver value

The Ideal Candidate will be:

- A Python wizard. Your interests go beyond simply writing code. You get excited about big picture design, style standards, and test cases.

- A wrangler of big code bases. You've developed within a large code base and know how to balance your learning between small details and the big picture to be effective quickly.

- Customer first. You love the process of creating, but at the end of the day, you know it's all about making the right decision for our customers.

- Interested in learning more data science. You know how to build a good model, maybe you learned in school or taught yourself, but you're hankering to do data science in the big leagues.

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.

Basic Qualifications:

-Bachelor's Degree plus 4 years of experience in data analytics, or Master's Degree plus 2 years of experience in data analytics, or PhD

-At least 2 years' experience in open source programming languages for large scale data analysis

-At least 2 years' experience with machine learning

-At least 2 years' experience with relational databases

Preferred Qualifications:

-PhD in "STEM" field (Science, Technology, Engineering, or Mathematics)

-At least 1 year experience working with AWS

-At least 4 years' experience in Python, Scala, or R for large scale data analysis

-At least 4 years' experience with machine learning

-At least 4 years' experience with SQL

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

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