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Quantitative Investment Analyst: Multi-Asset Class Solutions (all gender) Full/Part Time

Helvetia Versicherungen


For other companies, it's merely lip service. For us, it is a guiding principle: &Go. It stands for the trust we place in our employees and their abilities. Because we believe that shared success is only possible when everyone is given the scope they need to let their talents unfold in the best possible way. The best way not only for your personal development, but for the development of the company as a whole. We look forward to receiving your application.

Quantitative Investment Analyst: Multi-Asset Class Solutions (all gender) Full/Part Time

Quantitative Investment Analyst: Multi-Asset Class Solutions (all gender) Full/Part Time

Your responsibility

  • Responsible for the methods and development of tools used for Strategic Asset Allocation that include typical requirements and constraints of an insurer, like economic value generation, risk capital such as SST and Solvency II, liquidity, ESG, accounting and other aspects
  • Further develop Asset Liability Management- and SAA-models to optimise group asset allocations and investment capital allocation while considering local legal entity considerations and constraints
  • ALM is an important area for Helvetia and QMA. Hence ALM experience would be welcome. For candidates not proficient in ALM we would expect willingness to familiarise themselves with ALM.
  • Develop new investment strategies for Tactical Asset Allocation, build quantitative models to cull investment opportunities. Typical steps include: develop models based on academic research, build prototypes in R / Python, backtesting, simulation, stress-testing, presentation of results, bring the production-ready tool on the Helvetia cloud platform, connect to databases
  • Enhance efficiency of our derivatives overlay for equities & credit by determining optimal instruments and parameters to optimise pay off structure
  • Suggest improvements to our liability representation, e.g., to describe mismatches between assets and liabilities and ways to mitigate
  • Actively liaise with internal colleagues across the Asset Management and Helvetia organisation to enhance the value generation of our activities and services to our clients
    • This position is to be filled with a workload of 80% -100% and job-sharing may be possible

Your qualification

  • Master's or PhD in maths, physics, engineering, econometrics, finance or similar with quantitative focus
  • CFA, FRM, CQF or similar and/or interest in working towards such
  • Interest in digital topics: quantitative investing, programming, visualisation
  • Essential are coding skills in R, Python, VBA and/or other coding languages
  • Experience / practical knowledge with / interest in applying quantitative models / Machine Learning methods to Finance. Examples are systematic trading strategies, risk models, stress tests, asset allocation, time series analysis, simulation, derivatives
  • Experience with information systems like Bloomberg, FactSet, Refinitiv etc.
  • Entrepreneurial spirit, eagerness to learn and to contribute to shape a modern company
  • Very good command of English. German not essential, but an advantage

Pivotal for this role are coding skills. Not all other mentioned skills are required in combination. Primarily wanted is strong interest in understanding and modelling financial markets.


Part-time or Full-time

With work experience

by appointment

Carola Betschart

Take the first step now by applying online. We only consider direct applications and kindly ask recruiting agencies not to send us candidates.

Working at Helvetia

At Helvetia we look for people with distinctive strengths and weaknesses – genuine personalities with a bold, wholehearted approach who will not be deterred by the odd headwind. After all, it's only by trying out new ideas and learning from them that we can move forward both as individuals and as a company. We place this confidence in all our employees and this is precisely what makes working for Helvetia so special. Our take on this: &Go.