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.

Team Description

Innovation is at the heart of everything we do at the Audit Analytics and Innovation Team. We're not a traditional Data Science team: we build creative ML solutions across multiple domains from AML/Fraud, Card interest calculation to Financial Service customer call transcripts intelligence. We build fast and evolve fast and the amount of learning of ML in business applications is multi-folds. We are also highly integrated and influential in building products and platforms, working with Product Managers, Engineers and Designers on a daily basis. If you love fast-paced, highly rewarding environments, and you love being a builder and communicator, this is the place for you.

As a Sr. Data Science Manager in the Audit Analytics & Innovation Team, 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 to build and deploy models and analytical solutions leveraging new data sources to provide powerful insights about our business.

Role Description

In this role, you will:

• Partner with a cross-functional team of data scientists, data analysts, risk professionals, software engineers, and product managers to manage the risk and uncertainty inherent in statistical models in order to lead Capital One to the best decisions, not just avoid the worst ones

• Leverage a broad stack of technologies - Python, R, Conda, Flask, Dash, AWS, Dask, Spark, and more - help uncover new trends and improve analysis

• Lead and mentor a team of data scientists to deepen their understanding and use of cutting edge data science and machine learning methods

• Implementand productionize models (regression models, machine learning models etc.) in Cloud based platforms to enable efficient and accurate model inference

• Productionize highly scalable data pipelines for faster feature changes and updates, and implementing data validation framework and quality tests

• Develop visualization tools to streamline model monitoring reports

• Investigate new technology to advance data management, model development and deployment and drive change in enterprise ML products

The Ideal Candidate is:

• Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You're not afraid to share a new idea.

• A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You're passionate about talent development for your own team and beyond.

• Technical. You're comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing data science solutions using open-source tools and cloud computing platforms.

• A data guru. "Big data" doesn't phase you. You have the skills to retrieve, combine, and analyze data from a variety of sources and structures. You know understanding the data is often the key to great data science.

Basic Qualifications:

• Bachelor's Degree plus 7 years of experience in data analytics, or Master's Degree plus 5 years of experience in data analytics, or PhD plus 2 years of experience in data analytics

• At least 3 years' experience in open source programming languages for large scale data analysis

• At least 3 years' experience with machine learning

• At least 3 years' experience with relational databases

Preferred Qualifications:

• PhD in "STEM" field (Science, Technology, Engineering, or Mathematics) plus 4 years of experience in data analytics

• At least 1 year of experience working with AWS

• At least 1 year of experience working with GraphML

• At least 2 year of experience managing people

• At least 2 year of experience working with Natural Language Processing models (e.g., Transformer)

• At least 5 years' experience in Python, Scala, Dask, Spark or R for large scale data analysis

• At least 5 years' experience with machine learning

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

No Agencies please.

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 4901-4920; Newark, New Jersey Ordinance 12-1630; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.

The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.

Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter.

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 1-800-304-9102 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).