Capital One
Principal Associate, Data Scientist - US Card (Emerging Fraud)
Capital One, Richmond, Virginia, United States, 23214
Principal Associate, Data Scientist - US Card (Emerging Fraud)
Join to apply for the Principal Associate, Data Scientist - US Card (Emerging Fraud) role at Capital One.
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 led to a Fortune 200 company and a leader in data‑driven decision‑making.
Team Description The Emerging Fraud team is seeking a hands‑on model developer to build and enhance our next‑generation fraud detection models. In this role, you will be instrumental in developing key initiatives with a particular focus on transaction fraud, applying machine learning to solve complex, real‑world challenges and directly stopping new fraud tactics.
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.
Flex your interpersonal skills to translate the complexity of your work into tangible business goals.
The Ideal Candidate Is
Customer first. You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it’s about making the right decision 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, 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 passionate about 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 and have experience with clustering, classification, sentiment analysis, time series, and deep learning.
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. You know understanding the data is often the 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:
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.
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.
PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field).
Preferred Qualifications
Master’s Degree in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics, or PhD in “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.
Salary and Compensation
Chicago, IL: $144,200 – $164,600
McLean, VA: $158,600 – $181,000
New York, NY: $173,000 – $197,400
Richmond, VA: $144,200 – $164,600
Other locations: subject to the pay range associated with that location.
Benefits Capital One offers a comprehensive, competitive, and inclusive set of health, financial, and other benefits that support your total well‑being. Eligibility varies based on full or part‑time status, exempt or non‑exempt status, and management level.
Equal Opportunity Employer 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. Capital One will consider qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries.
Application Information This role is expected to accept applications for a minimum of 5 business days.
No agencies please.
For technical support or questions about Capital One’s recruiting process, please send an email to Careers@capitalone.com.
#J-18808-Ljbffr
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 led to a Fortune 200 company and a leader in data‑driven decision‑making.
Team Description The Emerging Fraud team is seeking a hands‑on model developer to build and enhance our next‑generation fraud detection models. In this role, you will be instrumental in developing key initiatives with a particular focus on transaction fraud, applying machine learning to solve complex, real‑world challenges and directly stopping new fraud tactics.
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.
Flex your interpersonal skills to translate the complexity of your work into tangible business goals.
The Ideal Candidate Is
Customer first. You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it’s about making the right decision 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, 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 passionate about 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 and have experience with clustering, classification, sentiment analysis, time series, and deep learning.
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. You know understanding the data is often the 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:
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.
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.
PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field).
Preferred Qualifications
Master’s Degree in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics, or PhD in “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.
Salary and Compensation
Chicago, IL: $144,200 – $164,600
McLean, VA: $158,600 – $181,000
New York, NY: $173,000 – $197,400
Richmond, VA: $144,200 – $164,600
Other locations: subject to the pay range associated with that location.
Benefits Capital One offers a comprehensive, competitive, and inclusive set of health, financial, and other benefits that support your total well‑being. Eligibility varies based on full or part‑time status, exempt or non‑exempt status, and management level.
Equal Opportunity Employer 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. Capital One will consider qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries.
Application Information This role is expected to accept applications for a minimum of 5 business days.
No agencies please.
For technical support or questions about Capital One’s recruiting process, please send an email to Careers@capitalone.com.
#J-18808-Ljbffr