Head of Risk Modelling and Data Sciences

3 weeks ago


Abu Dhabi, United Arab Emirates Venture search Full time

-Venture search
Abu Dhabi, United Arab Emirates

Posted 1 hour ago Hybrid Permanent Competitive**Key Responsibilities**:

- Collaborate with business, functional, and risk colleagues to further develop and strengthen the risk analytics and reporting framework.
- Build various Risk models including but not limited to VAR. Run scenario analysis and stress testing to provide a quantitative view of risk.
- Identify possible traits/trends that may materialize into risk or are emerging risks using deep learning-based models. Accordingly, knowledge of Machine Learning language is essential.
- Enhance scientific decision making at our organization through modeling and quantitative analysis.
- Analyze enterprise risk data to gain insight into risk themes, trends, and patterns.
- Review external events and emerging risks to ensure they are considered in enterprise risk analytics and reporting.
- Manage, coach, and mentor one or two members of junior/semi-junior staff.

**Requirements**:

- Qualified to post-graduate level, in Mathematics, Financial Mathematics, Physics or Statistics (or equivalent qualification/experience). Data science/Machine Learning & AI as specialization is preferred.
- Minimum of 10-12 years of work experience in a similar role having led a small team of junior staff, with a minimum of 6 years of data science/modelling/mining experience.
- Strong technical expertise in risk modelling with an execution/delivery focus.
- Understanding of industry-wide risk modelling practices and trends.
- Ability to pull data to create machine learning models from finance, investment, and portfolio companies.
- Proven track record of building various risk models such as VAR, ICAR, Monte Carlo Simulation model, scenario analysis models, and stress testing.
- Ability to continuously improve risk reporting and build various models where required by other team members.
- Ability to interpret results in simple and laymen context.
- Highly numerate with a high level of general intelligence.


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