Member of the Global ALM and Strategic Asset Allocation Team in Munich. The job is primarily focused on developing quantitative methods, Machine learning algorithms and tools to support asset-liability management of Life/Health (L/H) investment portfolios.
- Develop expertise in L/H actuarial cash-flow models. Perform ALM analysis by simulating various what-if scenarios (e.g. changes in asset allocation) in the cash-flow models and analyzing the impact on various KPIs (e.g. Solvency- II, IFRS 9/17).
- Apply Machine learning techniques (supervised and unsupervised, such as gradient boosting and deep learning) for risk / return optimization for L/H portfolios. Develop and maintain end-to-end software prototypes (e.g. in Python/R).
- Further develop existing analytical models and tools to evaluate investment strategies and asset allocation decisions in L/H portfolios.
- Cooperate and share data science best practices with other teams within AIM and Operating Entities located in different countries.
- Master Degree in Finance, Economics or Quantitative subjects
- Very good IT and programming skills; knowledge of Python, Visual Basic, C/C++ or other programming languages is a plus
- First experience with Machine learning techniques
- Fluent English written and spoken; knowledge of German and/or another language is a plus
- 1-3 years of experience in investment function of insurance, banking or asset management company
- Good knowledge of capital markets, financial modeling and instruments including derivatives
- Good understanding of portfolio optimization techniques, accounting and insurance regulation
- Strong team player, responsible and dependable with entrepreneurial attitude
- Good presentation and communication skills