Associate Consultant - Risk Dynamics at McKinsey & Company
Who You'll Work With
You'll be based in our North American Knowledge Center in Waltham, Massachusetts and will work with the Risk Dynamics (RD) Team, which is part of McKinsey's global Risk Practice.
McK/RD is a specialized team conducting in-depth validation and model risk advisory services for banks, asset managers, insurance firms and other leading financial institutions. These assessments require a rigorous understanding of both underlying modeling techniques and the overall business context in which such models are being used. Our model validation and model risk advisory work spans multiple risk functions, markets, operating challenges and modeling techniques.
What You'll Do
You will help clients validate their models and assess their modeling frameworks across a variety of risk functions, including market and trading risk, credit risk and model risk management.
You will be part of a team of exceptional risk analytics professionals with similarly deep industry experience and will be expected to communicate complex analytics concepts in a clear and concise manner to key client stakeholders.
You will also have the opportunity to advance McKinsey's overall knowledge base by providing rigorous analysis to and problem solving for our proprietary knowledge investments. At more senior levels, you'll also focus on developing new analytical approaches and techniques, working with an outstanding knowledge structure and international network of experts in order to codify existing knowledge and develop new knowledge.
Some work at the client site is expected. Working on projects and exchanging experiences with your colleagues means you will face new intellectual challenges on a daily basis, while continuously building your methodological knowledge and skills.
- A track record of academic excellence including a Master's or PhD from a reputable college/university in a quantitative field such as economics, mathematics, computational finance, statistics, engineering or physics; industry qualifications including CFA, FRM, PRM or similar would be considered an asset
- Interest in advanced quantitative modeling techniques within a financial services related industry (e.g., banking and securities, asset management)
- Experience in model development, validation and benchmarking, specifically related to single and multifactor models, and other modeling techniques (Merton, Longstaff-Schwartz, Black-Sholes, etc.) within a regulatory context (CCAR) is appreciated
- Exceptional verbal and written communication skills, especially around translating technical knowledge into forms that can be digested by leadership and non-technical project teams; ability to produce independent opinion and actionable recommendations
- Understanding of financial mathematics including stochastic calculus and probability theory, as well as derivative pricing models and other numerical techniques across a variety of asset classes (e.g., equities, rates, credit, FX and commodities)
- Experience programming in a modern scientific language (e.g., Python, Matlab, R) with some experience with Machine Learning, Java, C#, C++ or C. Knowledge of SQL, SAS and VBA would be a plus
- Knowledge of VaR (historic, parametric, Monte Carlo), EOD or intra-day risk and valuation as well as stress-testing and scenario analysis is ideal
- Travel up to 50%
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