We are looking for a highly talented individual with a strong quant background who is eager to contribute to the improvement and further development of Swiss Re's investment strategy and asset allocation process. Do you enjoy working in a highly team-oriented way and with high standards with regards to rigor and academic foundation? Then this opportunity could be for you!
About the Role
As part of the Asset Allocation Team, your focus will be on:
1. Collaborate on further developing Swiss Re's derivatives strategies and asset allocation process by means of utilizing advanced statistical analysis, and programming skills to improve portfolio construction, generate insights, identify market trends/opportunities, and make data-driven investment decisions across and within all liquid asset classes, derivatives, and private markets investments.
2. Team up with the development, maintenance, and documentation of models used for asset allocation, portfolio construction, and risk management.
3. Regular internal presentations of research work and contributing to writing research notes.
4. Contribute to data quality assurance, as well as performance and risk monitoring of the investment decisions.
5. Prepare key materials and analysis for various committees.
About the Team
Swiss Re Asset Management manages the assets generated from Swiss Re core insurance and reinsurance business. We drive sustainable performance by following a disciplined, long-term oriented investment approach and focus on a high-quality investment portfolio. As a global team of investment professionals, we ensure a strong contribution to Swiss Re's financial performance. In addition, we also support the company's thought leadership on long-term and responsible investing themes, and act as a "Centre of Excellence" for financial market expertise.
The role is an integral part of the Asset Allocation team, responsible for formulating the group investment strategy, asset allocation and steering listed equity and derivatives investments.
About You
You are a proactive and hands-on teammate with an entrepreneurial mindset and the flexibility to adapt to a fast-changing environment. As a fast learner with a well-organized, rigorous and structured approach to problem solving you are able to maintain high quality even under time pressure.
1. Master's degree in Financial Mathematics, Financial Engineering, (Quantitative) Finance, Economics, or related fields.
2. At least 3 years of experience in a comparable role.
3. Experienced with asset pricing & allocation models and econometrics.
4. Proficiency in MS Office applications and Bloomberg skills.
5. Strong knowledge of Python and at least one other programming language (previous contributions to large IT/Python projects is a plus).
6. Excellent English skills required.
About Swiss Re
Swiss Re is one of the world's leading providers of reinsurance, insurance and other forms of insurance-based risk transfer, working to make the world more resilient. We anticipate and manage a wide variety of risks, from natural catastrophes and climate change to cybercrime. We cover both Property & Casualty and Life & Health. Combining experience with creative thinking and cutting-edge expertise, we create new opportunities and solutions for our clients. This is possible thanks to the collaboration of more than 14,000 employees across the world.
Our success depends on our ability to build an inclusive culture encouraging fresh perspectives and innovative thinking. We embrace a workplace where everyone has equal opportunities to thrive and develop professionally regardless of their age, gender, race, ethnicity, gender identity and/or expression, sexual orientation, physical or mental ability, skillset, thought or other characteristics. In our inclusive and flexible environment everyone can bring their authentic selves to work and their passion for sustainability.
If you are an experienced professional returning to the workforce after a career break, we encourage you to apply for open positions that match your skills and experience.
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Reference Code: 132478
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