Principal Quantitative Analyst, Pay Equity - People Strategy & Analytics
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 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.
People Strategy & Analytics is an emerging field where Capital One is on the leading front. Our team brings data, analytics, and insights to shape critical talent decisions and strategy at Capital One. We work closely with HR partners and senior executives in shaping talent policy, automating real-time data, and improving talent decision-making. The team is composed of people with diverse skills and backgrounds including: data analysts and engineers, product managers, data scientists, consultants and strategists, business analysts, HR specialists, economists, and Industrial Organizational Psychologists.
Responsibilities and Skills:
Partner with cross-functional teams from Legal and Human Resources to assess Capital One's compensation system.
Utilize Python, SQL, and Quicksight to build modular, scalable, statistical models and reporting infrastructure and dashboards that will provide key insights about pay equity & fairness.
Provide insights that drive decisions and help shape policy impacting 50,000+ associates.
Flex your interpersonal skills to translate the complexity of statistical model results into tangible insights and actionable recommendations.
Apply root cause analysis, such as causal inference, to answer why an observed phenomenon happens and suggest actions that could effectively address concerns.
Successful candidates would possess:
Strong understanding of quantitative analysis methods in relation to financial institutions.
Demonstrated track record in machine learning and 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.
Proficiency in key econometric and statistical techniques (such as predictive modeling, logistic regression, survival analysis, panel data models, design of experiments, decision trees, machine learning methods).
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 or PhD in Statistics, Economics, Mathematics, Operations Research, Engineering, Physics or related discipline.
At least 3 years of experience in statistical techniques such as regression, root cause analysis, causal inference, classification and clustering.
At least 3 years of experience with developing and implementing models using modern scripting languages (Python, R or other statistical languages).
At least 3 years of experience working with large-scale, cloud-based coding environments and databases (Python, SQL or other data manipulation languages).
At least 1 year of experience in consulting.
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.
Richmond, VA: $144,200 - $164,600 for Prin Assoc, Quant 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 committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth, or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state, or local law. 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.