Director, Data Science

McLean 1 (19050), United States of America, McLean, Virginia

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.

Director, Data Science

Director, 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.

Department Summary:

In Capital One's Model Risk Office, we defend the company against model failures and find new ways of making better decisions. Model failures happen in a fascinating nexus of people, management and incentive structures, processes, technology, feedback loops, and unexpected external events... and it is our job to learn from past mistakes and develop increasingly powerful techniques to avoid their repetition. Today, Capital One is transforming its data infrastructure and modeling methodologies to build on its competitive advantage as a "Machine Learning company". This gives us an unprecedented opportunity to cultivate best practices and project them throughout the company.

On any given day you'll be:

-Assessing, critiquing, and at times defending state-of-the-art decision-making systems to internal and regulatory partners

-Evaluating deployment architecture and code quality for a new machine learning system

-Overseeing development of benchmark and challenger models to stress test critical modeling decisions

-Writing blog posts or delivering large-scale presentations to introduce our modeling community to emerging best practices

-Using modern computing tools (e.g., Spark, H2O, AWS) to perform an analysis of bias in a model's training data

-Reading up on a new modeling algorithm that the business is starting to use

-Developing software tools that support well-managed model development and maintenance

The Ideal Candidate will be:

-Technical: You have hands-on experience developing data science solutions, from concept to production, and selecting the right tool for the job at hand. You understand modern cloud computing. You have experience prototyping and implementing data science solutions in an enterprise. You know R, Scala, or Python.

-Communicator: You can communicate complex ideas clearly. Your team knows their priorities and you manage expectations with your broader cross-functional stakeholder network ad leadership team

-Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art algorithms and models.

-Business-Minded. You can understand how to make tradeoffs and partner effectively to drive impactful business outcomes.

-Leader. You challenge conventional thinking and traditional ways of operating and you influence stakeholders to improve the status quo.

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 8 years of experience in data analytics, or Master's Degree plus 6 years of experience in data analytics, or PhD plus 4 years of experience in data analytics

-At least 3 years' coding experience with open source programming languages such as R, Python, or Scala

-At least 3 years' experience developing commercial data science solutions leveraging one or more of the following: operations research, natural language processing, machine learning, deep learning, video/image analysis, or time-series analysis.

Preferred Qualifications:

-Master's Degree in a "STEM" Major (Science, Technology, Engineering, or Math) plus 6 years of experience in data analytics, or a PhD in a "STEM" Major plus 4 years of experience in data analytics
-At least 1 year experience working with AWS, Azure, or similar cloud platform
-At least 5 years' experience developing commercial solutions in Python, Scala, or R
-At least 5 years' experience developing commercial data science solutions leveraging one or more of the following: operations research, natural language processing, machine learning, deep learning, video/image analysis, or time-series analysis.
-At least 3 years of experience mentoring junior data scientists and providing technical governance and oversight

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


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