You’ll join our global Risk Practice in one of our European offices and be part of the Risk Dynamics team.
Consultant (m/f/d) - Risk Dynamics
Risk Dynamics helps clients to create sustainable modelling and analytics platforms to support their businesses in a data-driven world. From core regulatory capital and risk models, to business decision analytics and model risk management, we create value by improving performance across the model lifecycle.
Our experienced team incorporates risk specialists, quantitative experts, and business professionals, empowering us to offer our clients a unique variety of skills in risk management, business, and regulatory compliance. While we tailor every service to suit each client’s need, our identity is unwavering, with bedrock values including excellence, teamwork, integrity, and innovation.
What you'll do
You will help clients develop, refine and review their models and assess their frameworks for model development and model risk management across a variety of risk functions, including credit risk, market and trading risk, climate risk, financial crime and compliance, and wider applications such as cyber.
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.
- Advanced degree or PhD in a quantitative field such as Financial Engineering, Applied Finance/Statistics/ Mathematics, Computer Science
- 5+ years of relevant experience in quantitative analysis/modeling at a financial institution or consulting firm
- Experience in development, implementation and testing of risk models (vendor or “in-house” models)
- Experience in 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
- Proven knowledge in applying machine learning algorithm such as Neural Networks, Support Vector Machines, and CART, etc.
- Ability to work collaboratively in a team environment
- Ability to work effectively with people at all levels in an organization
- Ability to communicate complex ideas effectively, both verbally and in writing, in English and the local office language(s)
- Willingness to travel