Director, Data Science
Capital One
Director, Data Science
Job Description
Overview
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 Science Leader 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.The Intelligent Foundations and Experiences (IFX) group is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering. The Emerging AI Patterns team within IFX group is a new strategic initiative to explore and operationalize cutting-edge AI paradigms like Agentic frameworks, multi-agent collaboration. We are specifically focused on revolutionizing how Capital One develops, deploys, and manages a large number of machine learning models through Agentic AI systems.In this role, you will:Partner with a cross-functional team of software engineers, distinguished researchers, and solutions architects to drive great decisions through modeling
Define and drive towards an end state that is based on simplicity and the adoption of digital technologies, cloud hosting, and open source software.
Distill the details of complex interconnected modeling systems to influence senior business leaders on model strategy, business use, and risks
Assess, challenge, and at times defend state-of-the-art decision-making systems to internal and regulatory partners
Shape our practice of building machine learning models, from design through training, evaluation, validation, and implementation
Oversee development of benchmark and challenger models to stress test critical modeling decisions
A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo.
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.
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.
Statistically-minded. You’ve built models, validated them, and backtested them. You know how to interpret a confusion matrix or a ROC curve. You have experience with clustering, classification, sentiment analysis, time series, and deep learning.
Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date:
A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 9 years of experience performing data analytics
A Master's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration plus 7 years of experience performing data analytics
A PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 4 years of experience performing data analytics
At least 4 years of experience leveraging open source programming languages for large scale data analysis
At least 4 years of experience working with machine learning
At least 4 years of experience utilizing relational databases
PhD in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 5 years of experience in data analytics
At least 5 years of experience in Python, Scala, or R for large scale data analysis
At least 5 years of experience with machine learning
At least 1 year of experience working with AWS
At least 5 years of experience with complex architectural patterns (SOA), building APIs, microservices, and event streams
At least 5 years of experience with DevOps or DevSecOps and building CI/CD pipelines using Jenkins, Artifactory, Chef, Ansible, AWS CloudFormation templates, GitHub, and Sonar
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.Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at theCapital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.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 RecruitingAccommodation@capitalone.com. 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 Careers@capitalone.comCapital 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).
Locations
- McLean, Virginia, United States
- San Jose, California, United States
- New York, New York McLean, VirginiaMcLean
Salary
80,000 - 135,000 USD / yearly
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- machine learningintermediate
- data analyticsintermediate
- Pythonintermediate
- Scalaintermediate
- Rintermediate
- relational databasesintermediate
- AWSintermediate
- DevOpsintermediate
- CI/CD pipelinesintermediate
Required Qualifications
- Bachelor's Degree in quantitative field plus 9 years data analytics experience, or Master's plus 7 years, or PhD plus 4 years (experience)
- At least 4 years of experience leveraging open source programming languages for large scale data analysis (experience)
- At least 4 years of experience working with machine learning (experience)
- At least 4 years of experience utilizing relational databases (experience)
- PhD in STEM field plus 5 years experience (preferred) (experience)
Responsibilities
- Partner with cross-functional team to drive decisions through modeling
- Define and drive towards end state using digital technologies and cloud hosting
- Distill complex modeling systems to influence senior business leaders
- Assess and defend decision-making systems to internal and regulatory partners
- Shape practice of building machine learning models from design through implementation
- Oversee development of benchmark and challenger models
Benefits
- general: comprehensive, competitive, and inclusive set of health, financial and other benefits
Answer 10 quick questions to check your fit for Director, Data Science @ Capital One.
Related Books and Jobs
Director, Data Science
Capital One
Director, Data Science
Job Description
Overview
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 Science Leader 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.The Intelligent Foundations and Experiences (IFX) group is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering. The Emerging AI Patterns team within IFX group is a new strategic initiative to explore and operationalize cutting-edge AI paradigms like Agentic frameworks, multi-agent collaboration. We are specifically focused on revolutionizing how Capital One develops, deploys, and manages a large number of machine learning models through Agentic AI systems.In this role, you will:Partner with a cross-functional team of software engineers, distinguished researchers, and solutions architects to drive great decisions through modeling
Define and drive towards an end state that is based on simplicity and the adoption of digital technologies, cloud hosting, and open source software.
Distill the details of complex interconnected modeling systems to influence senior business leaders on model strategy, business use, and risks
Assess, challenge, and at times defend state-of-the-art decision-making systems to internal and regulatory partners
Shape our practice of building machine learning models, from design through training, evaluation, validation, and implementation
Oversee development of benchmark and challenger models to stress test critical modeling decisions
A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo.
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.
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.
Statistically-minded. You’ve built models, validated them, and backtested them. You know how to interpret a confusion matrix or a ROC curve. You have experience with clustering, classification, sentiment analysis, time series, and deep learning.
Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date:
A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 9 years of experience performing data analytics
A Master's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration plus 7 years of experience performing data analytics
A PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 4 years of experience performing data analytics
At least 4 years of experience leveraging open source programming languages for large scale data analysis
At least 4 years of experience working with machine learning
At least 4 years of experience utilizing relational databases
PhD in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 5 years of experience in data analytics
At least 5 years of experience in Python, Scala, or R for large scale data analysis
At least 5 years of experience with machine learning
At least 1 year of experience working with AWS
At least 5 years of experience with complex architectural patterns (SOA), building APIs, microservices, and event streams
At least 5 years of experience with DevOps or DevSecOps and building CI/CD pipelines using Jenkins, Artifactory, Chef, Ansible, AWS CloudFormation templates, GitHub, and Sonar
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.Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at theCapital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.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 RecruitingAccommodation@capitalone.com. 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 Careers@capitalone.comCapital 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).
Locations
- McLean, Virginia, United States
- San Jose, California, United States
- New York, New York McLean, VirginiaMcLean
Salary
80,000 - 135,000 USD / yearly
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- machine learningintermediate
- data analyticsintermediate
- Pythonintermediate
- Scalaintermediate
- Rintermediate
- relational databasesintermediate
- AWSintermediate
- DevOpsintermediate
- CI/CD pipelinesintermediate
Required Qualifications
- Bachelor's Degree in quantitative field plus 9 years data analytics experience, or Master's plus 7 years, or PhD plus 4 years (experience)
- At least 4 years of experience leveraging open source programming languages for large scale data analysis (experience)
- At least 4 years of experience working with machine learning (experience)
- At least 4 years of experience utilizing relational databases (experience)
- PhD in STEM field plus 5 years experience (preferred) (experience)
Responsibilities
- Partner with cross-functional team to drive decisions through modeling
- Define and drive towards end state using digital technologies and cloud hosting
- Distill complex modeling systems to influence senior business leaders
- Assess and defend decision-making systems to internal and regulatory partners
- Shape practice of building machine learning models from design through implementation
- Oversee development of benchmark and challenger models
Benefits
- general: comprehensive, competitive, and inclusive set of health, financial and other benefits
Answer 10 quick questions to check your fit for Director, Data Science @ Capital One.
Related Books and Jobs