Master’s or PhD and strong academic record 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
2+ years of relevant professional/industry experience with a focus on risk management, advanced predictive modeling techniques and/or model validation, preferably in retail or commercial credit risk modeling (PD, LGD, EAD)
Understanding of financial industry regulations and practices related to model development, capital requirements, and model validation (SR 11-07)
Knowledge of VaR (historic, parametric, MonteCarlo), EOD or intra-day risk & valuation, as well as stress-testing and scenario analysis
Familiarity in one of the following machine learning / AI areas: natural language processing, deep learning, anomaly detection, graph-based techniques, or neural networks
Exceptional verbal and written communication skills
Ability to translate technical knowledge in a way that can be digested by leadership and non-technical project teams
Ability to produce independent opinion and actionable recommendations
Experience programming (beyond simple scripts) in a modern scientific language (e.g., Python, Matlab, R) and experience with TensorFlow, Spark, Java, C#, C++, or C. Knowledge of SQL and SAS would be a plus
Demonstrated success in client-facing roles (consulting experience highly desired)
Global mindset; able to appreciate differences in market needs, competitive environment, and cultural norms across multiple countries
Willingness to travel up to 50%
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 team, which is part of McKinsey’s global Risk practice.
Risk Dynamics 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.
McKinsey fosters innovation driven by analytics, design thinking, mobile and social by developing new products/services and integrating them into our client work. It is helping to shift our model toward asset-based consulting and is a foundation for, and expands our investment in, our entrepreneurial culture. Through innovative software as a service solutions, strategic acquisitions, and a vibrant ecosystem of alliances, we are redefining what it means to work with McKinsey.
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. We are therefore looking for candidates who can establish connections between sophisticated modeling techniques and strategic decision-making processes. We have a global client base and you will be exposed to a highly international environment.
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.
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.