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

Manager, Data Science - Automation Excellence

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.

• Lead our code quality initiative, defining the vision and roadmap for the effortrole and carrying it out across the Retail Bank
• Present the code quality initiative and progress to both leaders and peers within the Bank and across the company, while driving adoption throughout the team
• Evaluate Machine Learning pipelines and Enterprise offerings to coach the team towards making the best development and deployment decisions for their use cases
• Leverage expertise on platforms and software best practices to enable and improve data scientists' code resiliency and performance
• Develop and maintain software tools, playbooks, and documentation to further drive engineering practices that rapidly lead to high performance models
• Curate or create training for software development best practices for data scientist mastery with tools used on model build and execution platforms

• Technical. You're experienced with open source languages and how they're used in artificial intelligence and machine learning. You understand what can and should be automated and standardized. Modular code powering real-time predictive applications running in 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 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 and make work exceptionally transferable through leveraging existing libraries/platforms as well as creating new modules where needed. Overall, you help others achieve a high level of coding maturity and be self-sufficient when putting work into production on a cloud infrastructure.
• Detail Oriented. Pre-commit hooks are as automatic as putting your seatbelt on when you get behind the wheel. You appreciate elegance and efficiency in code. You believe the little things add up and you can show the value of paying attention to the finer points of coding.
• Collaborative: 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.

• Currently has, or is in the process of obtaining a Bachelor's Degree plus 6 years of experience in data analytics, or currently has, or is in the process of obtaining a Master's Degree plus 4 years of experience in data analytics, or currently has, or is in the process of obtaining PhD plus 1 year of experience in data analytics, with an expectation that required degree will be obtained on or before the scheduled start date
• 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

• PhD in "STEM" field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics
• At least 1 year of experience working with AWS
• At least 4 years' experience in Python, particularly Pandas, Dask, or Spark for large scale data analysis
• At least 4 years' experience with custom code-driven machine learning projects using packages such as scikit-learn, H2O, xgboost, PyTorch, JAX, etc. (i.e., not GUI-driven ML)
• At least 4 years' experience with SQL