Manager - Risk Modelling- AI / ML - Amsterdam

The key element of this role is strong Risk Modelling experience- to support the continued growth of their Risk Modelling desk and related projects. This role will be within the firm’s GRC (Governance, Risk and Compliance) team, which is known for its experienced Consultants and cutting-edge solutions enabling organizations to cost-effectively manage risks initiatives and controls.

Entrepreneurial Set-up and Autonomy- This role is best suited for a Quantitative Risk professional with an entrepreneurial mind-set since there is a healthy dose of freedom in this role. One can choose their own internal “Project Sponsor”, translating into greater autonomy in deciding the kind of projects they would like to work on.

Steep Learning Curve & Bigger Leadership roles- The respective Quantitative Risk Manager has the freedom to lead respective Risk focused projects (in line with their experience and expertise) and have a greater flexibility in driving the project with their vision. On the other hand, this is a great platform for a Senior Consultant looking to gain execution - and leading exposure by working with Senior Quantitative Risk Specialists who would groom these junior resources to take on bigger roles within the desk.

Client Interface and Exposure- This role is a front-end, client facing opportunity. Depending on your seniority and experience you have the liberty to build your client network and develop relationships with clients and associates. You will also be able to communicate clearly and gain the trust of your clients, which gives you an opportunity to create your own niche within the GRC desk in line with your entrepreneurial outlook.

Prolific Clientele- Due to the diverse and expansive set of clients of the GRC desk, you would work for market and industry leaders, Global Conglomerates & Multinationals.

There is an element of Internal Audit involved in this role. As a trend, Clients are increasingly requesting internal audits due to the dynamic nature of their business and changing ECB regulations among others. With these changing market dynamics, internal audit is often elevated from pure compliance to a function that regularly reviews the risk profile for emerging risks and identifies trends as it keeps its finger on the pulse of business performance and is hence more content driven.

The 3rd LOD needs to know more and more about the business to be in line with the ECB guidelines. The firm keeps up with these trends and requirements via data modelling focused auditing using technologies like Artificial Intelligence and Machine Learning. Knowledge on Internal Audit/Assurance space is not a must, this can be trained on the job.

How do they distinguish themselves from their competitors?

1. Real content-based knowledge

2. They listen to the customer and look for the solution together instead of slightly adjusting the so called 'own' model and pushing it into the organization (which sometimes seems to be the case with other consultancies)

3. Put together a solution and take the customer on that journey – maximum exposure – leading to a solution which is a more permanent one

4. Soft skills - involved, friendly and professional

Profile needed:

• MSc in a quantitative subject (Mathematics, Statistics, Applied Mathematics, Mathematical Finance, Physics, etc)
• Experience in risk-modelling (model development or validation)
• Experience in market risk or/and counterparty risk modelling
• Experience with other risk models (Economic Capital, Stress Testing, etc.)
• Strong background in Math and Probability theory - applied to finance.
• Good understanding of financial products.
• Good programming level in Python or R or equivalent.
• Awareness of the latest technical developments in financial mathematics, pricing, and risk modelling
• Up-to-date knowledge of regulatory capital requirements for market and credit risk
• Understanding of Monte-Carlo Simulations

Responsibilities:

• Quantitative analysis and review of model frameworks, assumptions, data, and results
• Designing, modelling and prototyping challenger models when required • Continuous interaction and collaboration with stakeholders from a wide range of internal business areas, internal and external audit as well as supervisory authorities
• Testing models numerical implementations and reviewing documentations
• Checking the adherence to governance requirements
• Documentation of findings invalidation reports, including raising recommendations for model improvements
• Ensuring models are validated in line with regulatory requirements and industry best practice
• Tracking remediation of validation recommendations

We look forward to your application.

Gryphon Search