Position: Internship

Job type: Contract

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Job content

Job Description

Tensor Technologies is a proprietary high-frequency trading firm in the heart of Switzerland. We build next-generation algorithmic trading strategies and systems using applied machine learning techniques and cutting-edge technology. Leveraging our fully automated setup, we trade different financial assets on various electronic exchanges around the world. Our hierarchy is flat, we value teamwork and guide new joiners towards having a trading impact from very early onwards.

This is a unique opportunity in Switzerland. Our quant researcher internship is your chance to experience high-frequency trading (HFT). You’ll discover how you can apply statistical techniques to high-frequency financial data, train algorithms to learn new patterns and translate signals into profitable strategies. You’ll meet and collaborate with the full team of Tensor while being assigned to a mentor who’ll coach you through the internship.

Requirements
  • Final/penultimate year student in Statistics, Mathematics, Physics or a related technical field
  • Team player
  • Outstanding analytical skills with the ability to learn quickly
  • Proficient experience in programming languages, preferably Python or C++
  • Genuine interest in financial markets, though no prior knowledge or experience is required
  • Full time availability for at least three months
What we offer:
  • Opportunity to work alongside experienced traders and researchers in the low latency trading space
  • Ability to work with a cutting-edge data and software stack, with access to our high performance computing platform
  • Mentorship and guidance from researchers and developers to sharpen your data and dev skills
  • Competitive salary
  • Possibility of full-time offer upon completion of the internship
The timing and duration of the internship will be decided depending on the time constraints of the candidates. While our ideal start time for the internship is around the second half of 2022, we are open to accommodate for individual situations.
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Deadline: 05-05-2024

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