Capital One
Principal Associate, Data Scientist - US Card (BC&P Fraud)
Capital One, New York, New York, us, 10261
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 relational databases, cutting‑edge technology in 1988. Fast‑forward a few years, and this innovation and our passion for data has grown Capital One into a Fortune 200 company and a leader in data‑driven decision‑making. As a Data Scientist, 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 pain in their financial lives.
Team Description The Business Cards and Payments Fraud Modeling team is responsible for protecting this critical business segment from fraud. This role serves as a key model developer with a technical, hands‑on focus on this portfolio. The core responsibility is to dive deep into data to design, build, and implement new features that capture emerging fraud patterns. This work directly enhances the team's modeling capabilities and safeguards our Business Cards and Payments customers.
Role Description
Partner with a cross‑functional team of data scientists, software engineers, and product managers to deliver a product customers love
Leverage a broad stack of technologies—Python, Conda, AWS, H2O, Spark, and more—to reveal insights hidden within huge volumes of numeric and textual data
Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation
Use interpersonal skills to translate the complexity of your work into tangible business goals
The Ideal Candidate is
Customer first: you love analyzing and creating, and share our passion to do the right thing for our customers
Innovative: you continually research and evaluate emerging technologies, staying current on state‑of‑the‑art methods and seeking opportunities to apply them
Creative: you thrive on bringing definition to big, undefined problems; you love asking questions and pushing hard to find answers, and you’re not afraid to share new ideas
A leader: you challenge conventional thinking and work with stakeholders to identify and improve the status quo; you are 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 with cloud‑based data science solutions
Statistically‑minded: you’ve built, validated, and backtested models and know how to interpret a confusion matrix or ROC curve; experience with clustering, classification, sentiment analysis, time series, and deep learning is required
A data guru: “big data” doesn’t faze you; you have the skills to retrieve, combine, and analyze data from a variety of sources and structures, understanding that data insight is key to great data science
Basic Qualifications
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 5 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 3 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)
Preferred Qualifications
Master’s Degree in a STEM field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics, or PhD in a STEM field
At least 1 year of experience working with AWS
At least 3 years’ experience in Python, Scala, or R
At least 3 years’ experience with machine learning
At least 3 years’ experience with SQL
Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
Salary ranges for this role are based on location and include a base salary as well as potential performance‑based incentive compensation. Salary and incentives are determined at the time of offer.
Capital One offers a comprehensive, competitive, and inclusive set of health, financial, and other benefits that support your total well‑being. Eligibility varies by full or part‑time status, exempt or non‑exempt status, and management level.
Capital One is an equal‑opportunity employer (EOE, including disability and veteran status) committed to non‑discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug‑free workplace.
Capital One will consider qualified applicants with a criminal history in a manner consistent with applicable laws governing background inquiries.
If you have visited our website in search of employment opportunities or wish to apply for a position and require an accommodation, please contact Capital One Recruiting at 1‑800‑304‑9102 or via email at RecruitingAccommodation@capitalone.com. All information provided will be kept confidential and used only to the extent required to provide reasonable accommodations.
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Team Description The Business Cards and Payments Fraud Modeling team is responsible for protecting this critical business segment from fraud. This role serves as a key model developer with a technical, hands‑on focus on this portfolio. The core responsibility is to dive deep into data to design, build, and implement new features that capture emerging fraud patterns. This work directly enhances the team's modeling capabilities and safeguards our Business Cards and Payments customers.
Role Description
Partner with a cross‑functional team of data scientists, software engineers, and product managers to deliver a product customers love
Leverage a broad stack of technologies—Python, Conda, AWS, H2O, Spark, and more—to reveal insights hidden within huge volumes of numeric and textual data
Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation
Use interpersonal skills to translate the complexity of your work into tangible business goals
The Ideal Candidate is
Customer first: you love analyzing and creating, and share our passion to do the right thing for our customers
Innovative: you continually research and evaluate emerging technologies, staying current on state‑of‑the‑art methods and seeking opportunities to apply them
Creative: you thrive on bringing definition to big, undefined problems; you love asking questions and pushing hard to find answers, and you’re not afraid to share new ideas
A leader: you challenge conventional thinking and work with stakeholders to identify and improve the status quo; you are 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 with cloud‑based data science solutions
Statistically‑minded: you’ve built, validated, and backtested models and know how to interpret a confusion matrix or ROC curve; experience with clustering, classification, sentiment analysis, time series, and deep learning is required
A data guru: “big data” doesn’t faze you; you have the skills to retrieve, combine, and analyze data from a variety of sources and structures, understanding that data insight is key to great data science
Basic Qualifications
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 5 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 3 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)
Preferred Qualifications
Master’s Degree in a STEM field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics, or PhD in a STEM field
At least 1 year of experience working with AWS
At least 3 years’ experience in Python, Scala, or R
At least 3 years’ experience with machine learning
At least 3 years’ experience with SQL
Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
Salary ranges for this role are based on location and include a base salary as well as potential performance‑based incentive compensation. Salary and incentives are determined at the time of offer.
Capital One offers a comprehensive, competitive, and inclusive set of health, financial, and other benefits that support your total well‑being. Eligibility varies by full or part‑time status, exempt or non‑exempt status, and management level.
Capital One is an equal‑opportunity employer (EOE, including disability and veteran status) committed to non‑discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug‑free workplace.
Capital One will consider qualified applicants with a criminal history in a manner consistent with applicable laws governing background inquiries.
If you have visited our website in search of employment opportunities or wish to apply for a position and require an accommodation, please contact Capital One Recruiting at 1‑800‑304‑9102 or via email at RecruitingAccommodation@capitalone.com. All information provided will be kept confidential and used only to the extent required to provide reasonable accommodations.
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