Tensor Technologies is looking for an enthusiastic and passionate Trader with 3+ years of commercial experience in leveraging large datasets and Machine Learning techniques for high-frequency-trading (HFT) strategy design. Tensor Technologies’ research and trading are driven by big data, and the resulting algorithms are run on high-performance hardware using software that is developed in-house.
Your main responsibilities:
- Design and prototype algorithmic HFT strategies to trade in electronic financial markets, leveraging the latest technologies to efficiently scale across many markets globally
- Research and prototype state-of-the-art Machine Learning models
- Work with large data sets, including unconventional data sources, to predict and test statistical market patterns
- Monitor the performance of the trading strategies and improve it further
- 3+ years of experience in researching, prototyping and running profitable algorithmic HFT strategies using Machine Learning, preferably on Futures
- PhD degree or a Master’s degree with relevant experience in Computer Science, Mathematics, Physics or a related field
- Excellent mathematical abilities
- Excellent programming skills in Python
- Excellent knowledge of Machine Learning models and techniques
- Programming skills in Scala and Spark is a big plus
What we offer:
- We apply the newest technologies and strategies in order to gain advantage over our competitors.
- We rely on quick feedback loops and we release early and often to profit from incremental benefits as they are developed.
- You will be able to challenge your coding and trading skills and grow constantly while collaborating with like-minded experts in a dynamic environment that encourages continuous learning.
- Attractive office locations in the center of Switzerland in Zug and Zurich.
- The opportunity to join a team that has achieved considerable success in a relatively short amount of time and is now growing the business.
- A compensation and bonus scheme that’s unprecedented in the industry.
Please apply via our careers site.
We look forward to getting to know you!