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Manager, Data Science
Manager, Data Scientist, Retail Bank Data Science
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 Risk and Resiliency team in the Retail Bank builds the machine learning models that help our customers get an account, bank with the confidence that their accounts are secure, and get access to their money faster. We do data and model pipelining, machine learning, and well-managed model operations using Python, KFP, and ML libraries in our tech stacks.
Role Description In this role, you will:
Partner with a cross-functional team of data scientists, software engineers, and product managers to deliver an experience that helps us book more customers
Take a well-managed approach to building customer-facing decision products while also bolstering our defenses with governed vendor tools that fill a niche and complement our own models
Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation
Most critically, build connections with your partners to understand the fraud threats of today and tomorrow so you can devise a modeling roadmap that proxies fraud signal from our data, keeping the fraudsters out while making account opening a seamless experience for others
The Ideal Candidate is:
Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them.
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 and deploying 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 and an AUPRC view. You have experience with clustering, classification, sentiment analysis, time series, and deep learning.
Basic Qualifications:
A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 6 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 4 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 1 year of experience performing data analytics
At least 1 year of experience leveraging open source programming languages for large scale data analysis
At least 1 year of experience working with machine learning
At least 1 year of experience utilizing 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 5 years’ experience in Python, Scala, or R for large scale data analysis
At least 5 years’ experience with machine learning
At least 5 years’ experience with SQL
Previous experience with rare event prediction, especially fraud, for credit-like decisions strongly preferred
Salary and Benefits McLean, VA: $193,400 - $220,700 for Manager, Data Science. 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. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI).
Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well‑being.
EEO Statement Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non‑discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug‑free workplace.
Immigration Sponsorship Capital One will consider sponsoring a qualified applicant for employment authorization for this position.
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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 Risk and Resiliency team in the Retail Bank builds the machine learning models that help our customers get an account, bank with the confidence that their accounts are secure, and get access to their money faster. We do data and model pipelining, machine learning, and well-managed model operations using Python, KFP, and ML libraries in our tech stacks.
Role Description In this role, you will:
Partner with a cross-functional team of data scientists, software engineers, and product managers to deliver an experience that helps us book more customers
Take a well-managed approach to building customer-facing decision products while also bolstering our defenses with governed vendor tools that fill a niche and complement our own models
Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation
Most critically, build connections with your partners to understand the fraud threats of today and tomorrow so you can devise a modeling roadmap that proxies fraud signal from our data, keeping the fraudsters out while making account opening a seamless experience for others
The Ideal Candidate is:
Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them.
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 and deploying 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 and an AUPRC view. You have experience with clustering, classification, sentiment analysis, time series, and deep learning.
Basic Qualifications:
A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 6 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 4 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 1 year of experience performing data analytics
At least 1 year of experience leveraging open source programming languages for large scale data analysis
At least 1 year of experience working with machine learning
At least 1 year of experience utilizing 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 5 years’ experience in Python, Scala, or R for large scale data analysis
At least 5 years’ experience with machine learning
At least 5 years’ experience with SQL
Previous experience with rare event prediction, especially fraud, for credit-like decisions strongly preferred
Salary and Benefits McLean, VA: $193,400 - $220,700 for Manager, Data Science. 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. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI).
Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well‑being.
EEO Statement Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non‑discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug‑free workplace.
Immigration Sponsorship Capital One will consider sponsoring a qualified applicant for employment authorization for this position.
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