Capital One Principal Quantitative Analyst– Model Validation in McLean, Virginia
McLean 1 (19050), United States of America, McLean, Virginia
At Capital One, we’re building a leading information-based technology company. Still founder-led by Chairman and Chief Executive Officer Richard Fairbank, Capital One is on a mission to help our customers succeed by bringing ingenuity, simplicity, and humanity to banking. We measure our efforts by the success our customers enjoy and the advocacy they exhibit. We are succeeding because they are succeeding.
Guided by our shared values, we thrive in an environment where collaboration and openness are valued. We believe that innovation is powered by perspective and that teamwork and respect for each other lead to superior results. We elevate each other and obsess about doing the right thing. Our associates serve with humility and a deep respect for their responsibility in helping our customers achieve their goals and realize their dreams. Together, we are on a quest to change banking for good.
Principal Quantitative Analyst– Model Validation
As a Principal Quantitative Analyst within the Model Risk Office, you will be part of the model validation team, working on the validation of stress testing models and Interest Rate and Liquidity Risk Management models. You will enhance your technical and analytical skills, while also working closely with business leaders to influence business strategy. With a network of over 200 quantitative analysts and statisticians, we’ve created a dynamic environment with plenty of room for you to learn, grow, and realize your full potential.
Specific responsibilities may include, but are not limited to:
Perform model validation for statistical and other quantitative models used in stress testing, interest rate risk, liquidity risk and deposit funding
Assess the quality and risk of model methodologies, outputs, and processes
Develop alternative model approaches to assess model design and advance future capabilities
Understand relevant business processes and portfolios associated with model use
Understand technical issues in econometric, statistical and machine learning methods and apply these skills toward assessing model risks and opportunities
Communicate clearly and concisely both verbally and through written communication via model validation reports and presentations
Master’s Degree in Financial Engineering, Quantitative Finance, Statistics, Economics, Mathematics, Operations Research, Engineering, Business or Physics
At least 1 year of experience in Financial Engineering or Financial Risk Management or Econometrics
At least 1 year of experience with large scale data analysis
At least 1 year of experience with Python or R
Doctorate in quantitative field
Proficiency in key financial engineering or econometric or statistical techniques
Strong experience in programming
2+ years of experience with large scale data analysis
2+ years of experience with Python, or R
Experience with machine learning
Strong verbal and written communication skills
Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.