- 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 repository 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 tools used 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 efficiency using the latest in distributed storage and compute paradigms to optimize performance
- Present the code quality initiative and progress 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 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.
- 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, 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
Preferred Qualifications: - 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
Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.
This role is expected to accept applications for a minimum of 5 business days.
No agencies please. Capital One is an equal opportunity employer committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.
If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.
For technical support or questions about Capital One's recruiting process, please send an email to
Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.
Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC). -
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Description
Center , United States of America, McLean, VirginiaManager, Data Science - ML Automation and Code Quality
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 passion for improving customer experiences. For that, our team writes lots of custom Python and Bash code to develop and deploy advanced AI/ML techniques. We care very deeply about doing things the right way, automating, standardizing, and removing barriers to getting things done quickly. Whether it's big or small data, our team's ability to turn that data into insights and insights into great decisions, hinges upon the code that makes it all work. 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:
