Master Thesis

  • Hours: 100%

  • Location: Zurich

  • Duration: up to 6 months, starting immediately

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.


We offer Master theses for students wishing to focus on the research and development of mathematical models, algorithms, computational methods and optimization frameworks applied to financial markets.

The topics include:

• Application of McKean Anticipative BSDE for Margin Valuation Adjustment (MVA) computations
• Approximation of derivative prices based on machine learning
• Conversational AI based on multi-document extractive text summarization
• Detecting exposure to business cycles
• Robust insurance claim forecasting
• Robust Portfolio Optimization in the Presence of Parameter Uncertainties

For more details, please refer to attached thesis proposals.


We are looking for a highly motivated student registered in a Master program at a recognized Swiss university, willing to focus his/her Master thesis on quant modeling in the context of the financial industry. The required qualifications are topic-specific; please refer to attached thesis proposals for details.


Quant Research team predominantly focuses on driving innovation efforts at swissQuant. We are active in the fields of machine learning, artificial intelligence, applied statistics, optimization and financial modelling, with applications in the financial sector. Our mandate consists in monitoring and investigation of new methodological advances, development of prototypes and innovation projects in collaboration with business areas.


Interested? Please register and upload your cover letter and CV/Recommendations in PDF format via

Master Thesis (PDF, 108 kb) Conversational AI (PDF, 344 kb) Derivative Pricing (PDF, 328 kb) Detecting exposure to Business Cycles (PDF, 330 kb) Margin Valuation Adjustment (PDF, 337 kb) Robust Insurance Claim Forescasting (PDF, 364 kb) Robust Portfolio Optimization (PDF, 456 kb)

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