Quantitative Analyst

  • Hours: 100%

  • Location: Zurich

  • Duration: permanent, start negotiable

swissQuant Group provides quantitative services, consultancy and products for financial and industrial clients, including a number of global Fortune 500 companies. Our business edge originates from the effective translation of Intelligent Technology into measurable, bottom-line client value. swissQuant Group is a privately held company incorporated in 2005 as a spin-off of ETH Zürich.

Position Overview

We are looking for a quantitative analyst to support our Quant Research team. The analyst will work on the development of new statistical approaches for multivariate time-series modelling and statistical estimation in portfolio risk and optimization context. The analyst will review recent academic work and try to find applications to concrete problems. Furthermore, the analyst will review and validate under the mandate of the internal Methodology Board newly developed risk and derivative models through extensive testing as well as methodological documentation and code reviews.

The job will allow the successful candidate to learn and investigate in depth different statistical models with concrete applications in the financial sector.

Desired Skills and Experience

To be a successful candidate, you must fulfil the following requirements:

  • PhD in Quantitative Finance, Statistics, Data Science or similar quantitative majors

  • Candidates with outstanding M.Sc. degrees (please provide final transcripts) or relevant work experience (>2 years) will be considered as well

  • Good knowledge of Python and Matlab/R is a must

  • Strong statistical knowledge including multivariate time-series models, Bayesian statistics, advanced MC methods and robust estimators

  • Working knowledge of stochastic processes and derivative pricing

  • Machine learning knowledge is a plus

  • Analytical, independent and creative thinking

  • Fluent spoken and written English

  • Eligible to live and work in Switzerland

Quant Analyst (PDF, 73 kb)

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