Manager, Data Science - Retail Bank

Center 2 (19050), United States of America, McLean, Virginia

Manager, Data Science - Retail Bank

​Data is at the center of everything we do. 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 computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives.

Team Description

The Retail Bank Data Science team has a relentless focus on innovation with a target towards improving customer experience. Our data science teams write lots of custom Python code to improve the customer experience and our business through machine learning applications. We care very deeply about doing things the right way, automating, and removing barriers to getting things done. Whether it’s big or small data, our teams’ ability to turn that data into insights and insights into great decisions hinges upon the code that makes it all work. And, the more time we can save through code that runs flawlessly and without intervention, the more time we have to deliver new insights.

Role Description

In this role, you will:

• Lead our code quality initiative, defining the vision for the role and carrying it out across the Retail Bank

• Leverage expertise on platforms and software best practices to enable and improve data scientists’ code resiliency and performance

• Partner with data scientists in the Bank and across the company to develop code and repo quality standards ( but not reinventing the wheel) and train data scientists to adopt and adhere to these standards with structured peer code reviews

• Develop or curate training for software development best practices for data scientist mastery on model build and execution platforms

• Devise roadmaps to ever increasing code quality maturity in our organization

• Communicate those standards and teach others how to achieve them

• Hold teams accountable for meeting the standards

• Host office hours or other avenues to assist data scientists in need of assistance on model build and execution platforms and tools

• Engage with the data science community to solicit feedback and lead virtual or in-person training sessions

• Develop and maintain up to date playbooks for the tools and development practices

• Evaluate existing ML pipelines and analyze computational optimizations using the latest in distributed storage and compute paradigms to optimize performance

• Present the code quality initiative to both leaders and peers within the Bank and across the company.

The Ideal Candidate is:

• Technical. You’re experienced with open source languages and how they’re used in machine learning. Code powering real-time predictive applications running on the cloud is kinda your thing.

• A Teacher. You know your way around a complex collaborative code base, but you still remember what it was like writing your first “hello world” script. You can articulate the why, the what, and the how of writing modular, unit-tested code so others can get on your level. The only thing better than writing your own masterful Python package is coaching someone else to leave their beloved Notebook behind and learn to do the same.

• A Self-Starter. You will own the mission to define the structure that leads our team to eliminate errors, automate everything, make their work exceptionally transferrable, and overall achieve a high level of coding maturity to be self-sufficient when putting their work into production on a cloud infrastructure.

• Detail Oriented. You care about tabs vs. spaces and pre-commit hooks are as automatic as putting your seatbelt on when you get behind the wheel. You believe the little things add up and you can show the value of paying attention to the finer points of coding.

• An Influencer: You work well with leaders and fellow data scientists to balance code quality needs with existing project timelines. You are able to incorporate opinions from various stakeholders to come up with a plan that serves the most good.

Basic Qualifications:

• Currently has, or is in the process of obtaining a Bachelor’s Degree plus 6 years of experience in data analytics, or currently has