Director, Quantitative Analysis - Commercial Credit Modeling Team

Director, Quantitative Analysis - Commercial Credit Modeling Team 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 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 Quantitative Analyst 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. Capital One’s Counterparty Risk Group has a $7B+ credit risk portfolio toward Financial Institutions across the Enterprise. We also extend credit risk management to the Global Payment Network and the Commercial Bank at the intersection of financial institutions and commercial lending. In the Counterparty Risk Group, you’ll get an opportunity to solve a diverse set of problems with a diverse set of tools. In some settings, you’ll leverage open source programming or cloud computing to predict credit risk events across complex datasets using statistical techniques. In other settings, you’ll get the opportunity to use completely different skill sets, blending business insights with quantitative tools when forecasting rare or unprecedented events. It’s a team full of exciting opportunities to solve a range of complex problems, generating insights for credit decision makers. Responsibilities and Skills: Communicate clearly and concisely both verbally and through written communication via model validation presentations and reports and presentations. Develop and implement strategies for statistical and financial models used to support Counterparty Credit Risk processes. Assess the quality and risk of model methodologies, outputs, and processes. Develop alternative approaches to model design and deployment capabilities. Apply expertise in econometric, statistical, and machine learning methods to generate insights in modeled risks. Identify opportunities to apply quantitative methods and automation solutions to improve business performance and process efficiencies. Expertise in quantitative analysis is central to our success in all markets. Our modelers thrive in a culture of mutual respect, excellence and innovation. Successful candidates would possess: Strong understanding of quantitative analysis methods relating to financial institutions and financial risk exposures. Demonstrated track-record in model development and/or validation. 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. Appreciation for processes, controls, and good governance. Ability to manage complex projects that require cross-team collaboration. Basic Qualifications: Currently has, or is in the process of obtaining one of the following with an exception that the required degree will be obtained on or before the scheduled start date: 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 in quantitative 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 in quantitative analytics At least 7 years of experience in each of the following skills through education or experience: Statistical or econometric modeling Linear and logistic regression Programming in R, Python, or SQL Presenting statistical concepts and research results to non-statistical audience? At least 7 years of experience in at least 3 of the following skills: Survival analysis modeling Time-series analysis Panel data (longitudinal data or cross-sectional time-series data) analysis Cross-sectional data analysis Machine learningAnalysis and management of large datasets (>1M records) Preferred Qualifications: 8 years of experience in Python, Scala, R or other statistical analyst software 8 years of experience with machine learning 3 years of experience managing people 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: $269,100 - $307,200 for Director, Quantitative AnalysisNew York, NY: $293,600 - $335,100 for Director, Quantitative Analysis 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). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. 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 for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations 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 View phone number on click.appcast.io or via email at View email address on click.appcast.io. 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 View email address on click.appcast.io Capital 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). Director, Quantitative Analysis - Commercial Credit Modeling Team 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 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 Quantitative Analyst 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. Capital One’s Counterparty Risk Group has a $7B+ credit risk portfolio toward Financial Institutions across the Enterprise. We also extend credit risk management to the Global Payment Network and the Commercial Bank at the intersection of financial institutions and commercial lending. In the Counterparty Risk Group, you’ll get an opportunity to solve a diverse set of problems with a diverse set of tools. In some settings, you’ll leverage open source programming or cloud computing to predict credit risk events across complex datasets using statistical techniques. In other settings, you’ll get the opportunity to use completely different skill sets, blending business insights with quantitative tools when forecasting rare or unprecedented events. It’s a team full of exciting opportunities to solve a range of complex problems, generating insights for credit decision makers. Responsibilities and Skills: Communicate clearly and concisely both verbally and through written communication via model validation presentations and reports and presentations. Develop and implement strategies for statistical and financial models used to support Counterparty Credit Risk processes. Assess the quality and risk of model methodologies, outputs, and processes. Develop alternative approaches to model design and deployment capabilities. Apply expertise in econometric, statistical, and machine learning methods to generate insights in modeled risks. Identify opportunities to apply quantitative methods and automation solutions to improve business performance and process efficiencies. Expertise in quantitative analysis is central to our success in all markets. Our modelers thrive in a culture of mutual respect, excellence and innovation. Successful candidates would possess: Strong understanding of quantitative analysis methods relating to financial institutions and financial risk exposures. Demonstrated track-record in model development and/or validation. 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. Appreciation for processes, controls, and good governance. Ability to manage complex projects that require cross-team collaboration. Basic Qualifications: Currently has, or is in the process of obtaining one of the following with an exception that the required degree will be obtained on or before the scheduled start date: 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 in quantitative 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 in quantitative analytics At least 7 years of experience in each of the following skills through education or experience: Statistical or econometric modeling Linear and logistic regression Programming in R, Python, or SQL Presenting statistical concepts and research results to non-statistical audience? At least 7 years of experience in at least 3 of the following skills: Survival analysis modeling Time-series analysis Panel data (longitudinal data or cross-sectional time-series data) analysis Cross-sectional data analysis Machine learning Analysis and management of large datasets (>1M records) Preferred Qualifications: 8 years of experience in Python, Scala, R or other statistical analyst software 8 years of experience with machine learning 3 years of experience managing people 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: $269,100 - $307,200 for Director, Quantitative AnalysisNew York, NY: $293,600 - $335,100 for Director, Quantitative Analysis 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). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. 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 for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations 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 View phone number on click.appcast.io or via email at View email address on click.appcast.io. 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 View email address on click.appcast.io Capital 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). #J-18808-Ljbffr itSMF USA