Capital One
2 days ago Be among the first 25 applicants
As a Quantitative Modeler 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 cloud 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.
This position is part of Capital One’s Credit Risk Management Modeling team. In this team, we use multiple cloud‑based open‑source technologies to develop econometric and machine learning models and analytics to predict and generate insight into Capital One’s risk and capital needs. We blend cutting‑edge quantitative methods with deep understanding of our business, data, and regulatory environment to build predictive models for credit and operational losses, volumes and outstanding balances in support of loss forecasting, CECL/allowance, stress testing, and capital allocation for Capital One. Our models and analyses inform earnings call prep, vertical resilience and downturn preparedness initiatives.
In this position, you’ll be part of a team tasked with ushering in the next wave of disruption to predictive modeling – using technology to build & deploy models and solutions leveraging new data sources to provide powerful new insights about our portfolio resilience and opportunities.
Responsibilities and Skills
Partner with the various lines of business to enhance modeling and analytical framework.
Work across Capital One entities to create novel analytical solutions to the challenging business problems.
Identify opportunities to apply quantitative methods and automation solutions to improve business performance and process efficiencies.
Collaborate in a cross‑disciplinary team to build cloud‑based solutions grounded in data.
Apply deep expertise in econometric, statistical and machine learning methods to generate critical insights and decision frameworks for our business and customers.
Provide technical guidance to business leadership.
Communicate technical subject matter clearly and concisely to individuals from various backgrounds.
Successful candidates would possess
Strong understanding of quantitative analysis methods in relation to financial institutions.
Demonstrated track‑record in machine learning and/or econometric analysis.
Experience utilizing model estimation tools.
Ability to clearly communicate modeling results to a wide range of audiences.
Drive to develop and maintain high quality and transparent model documentation.
Strong written and verbal communication skills.
Strong presentation skills.
Ability to fully own the model development process: from conceptualization through data exploration, model selection, validation, deployment, business user training, and monitoring.
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 Ph.D. in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field).
Preferred Qualifications
Ph.D. in Statistics, Economics, Mathematics, Financial Engineering, Operations Research, Engineering, Finance, Physics or related disciplines.
1+ year of experience with Python, R or other statistical analyst software.
2+ years of experience with data analysis.
1+ year of experience manipulating and analyzing large data sets.
Proficiency in key econometric and statistical techniques (predictive modeling, logistic regression, survival analysis, panel data models, design of experiments, decision trees, machine learning methods).
Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
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.
McLean, VA: $158,600 - $181,000 for Prin Assoc, Quant Analysis
This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long‑term incentives (LTI). Incentives could be discretionary or non‑discretionary depending on the plan.
Seniority level
Mid‑Senior level
Employment type
Full‑time
Job function
Design, Art/Creative, and Information Technology
Capital One is an equal opportunity employer (EOE, including disability/veteran) committed to non‑discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug‑free workplace. 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.
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.com.
#J-18808-Ljbffr
As a Quantitative Modeler 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 cloud 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.
This position is part of Capital One’s Credit Risk Management Modeling team. In this team, we use multiple cloud‑based open‑source technologies to develop econometric and machine learning models and analytics to predict and generate insight into Capital One’s risk and capital needs. We blend cutting‑edge quantitative methods with deep understanding of our business, data, and regulatory environment to build predictive models for credit and operational losses, volumes and outstanding balances in support of loss forecasting, CECL/allowance, stress testing, and capital allocation for Capital One. Our models and analyses inform earnings call prep, vertical resilience and downturn preparedness initiatives.
In this position, you’ll be part of a team tasked with ushering in the next wave of disruption to predictive modeling – using technology to build & deploy models and solutions leveraging new data sources to provide powerful new insights about our portfolio resilience and opportunities.
Responsibilities and Skills
Partner with the various lines of business to enhance modeling and analytical framework.
Work across Capital One entities to create novel analytical solutions to the challenging business problems.
Identify opportunities to apply quantitative methods and automation solutions to improve business performance and process efficiencies.
Collaborate in a cross‑disciplinary team to build cloud‑based solutions grounded in data.
Apply deep expertise in econometric, statistical and machine learning methods to generate critical insights and decision frameworks for our business and customers.
Provide technical guidance to business leadership.
Communicate technical subject matter clearly and concisely to individuals from various backgrounds.
Successful candidates would possess
Strong understanding of quantitative analysis methods in relation to financial institutions.
Demonstrated track‑record in machine learning and/or econometric analysis.
Experience utilizing model estimation tools.
Ability to clearly communicate modeling results to a wide range of audiences.
Drive to develop and maintain high quality and transparent model documentation.
Strong written and verbal communication skills.
Strong presentation skills.
Ability to fully own the model development process: from conceptualization through data exploration, model selection, validation, deployment, business user training, and monitoring.
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 Ph.D. in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field).
Preferred Qualifications
Ph.D. in Statistics, Economics, Mathematics, Financial Engineering, Operations Research, Engineering, Finance, Physics or related disciplines.
1+ year of experience with Python, R or other statistical analyst software.
2+ years of experience with data analysis.
1+ year of experience manipulating and analyzing large data sets.
Proficiency in key econometric and statistical techniques (predictive modeling, logistic regression, survival analysis, panel data models, design of experiments, decision trees, machine learning methods).
Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
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.
McLean, VA: $158,600 - $181,000 for Prin Assoc, Quant Analysis
This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long‑term incentives (LTI). Incentives could be discretionary or non‑discretionary depending on the plan.
Seniority level
Mid‑Senior level
Employment type
Full‑time
Job function
Design, Art/Creative, and Information Technology
Capital One is an equal opportunity employer (EOE, including disability/veteran) committed to non‑discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug‑free workplace. 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.
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.com.
#J-18808-Ljbffr