Graduate Quant Researcher

About Wintermute Wintermute is one of the largest crypto native algorithmic trading companies in digital assets. We provide liquidity across most cryptocurrency exchanges and trading platforms, a broad range of OTC trading solutions as well as support high profile blockchain projects and traditional financial institutions moving into crypto. Wintermute also has a Wintermute Ventures arm that invests in early stage DeFi projects. Wintermute was founded in 2017 and has successfully navigated industry cycles. Culturally, we combine the best of the two worlds: the technology standards of high‑frequency trading firms in traditional markets and the innovative and entrepreneurial culture of technology startups. To Wintermute digital assets is not just another asset class, we believe in the innovative potential of blockchain, the fundamental innovations, we have a long‑term view on the digital asset market and are taking a leadership position in building an innovative and compliant market. You can read more here. Working at Wintermute We are looking for a Graduate Quant Researcher. The ideal candidate would have strong quantitative and coding skills (Python). At Wintermute, you will be responsible for scaling and bringing our quantitative business to the next level. You will have the opportunity to cover all technologies (CeFi, DeFi), trading platforms and products (spot, derivatives, ETPs, etc.). You will work with other researchers, traders and developers to build trading strategies and improve existing algorithmic trading activities. Our experienced traders and developers will be on hand to provide advice and guidance, including the founders and management team. You will get a lot of independence and responsibility right away, and you'll learn at an unprecedented speed No legacy systems, no corporate bureaucracy, it is up to you to make an impact. Responsibilities Assist with improving our high‑frequency trading strategies. Apply statistical techniques to develop short‑term signals, with a time horizon from milliseconds to a few minutes. Lead research efforts to improve signals and optimise parameters through back testing, across a wide range of trading products and technologies. Proactively identify market microstructure patterns and trading opportunities by analysing vast quantities of tick level historical market data across many markets. Run simulations and model market for both liquid and illiquid assets. Improve and maintain supporting infrastructure in Python. Hard Skills Requirements Quantitative degree in Mathematics, Statistics, Computer Science, Physics or related qualitative field. Post‑graduate degrees may be a plus but not expected or required. Advanced Python coding skills. Experience and advanced knowledge of statistics/probability theory. Machine Learning experience. Quant Trader Track Experience in market making, including signal design and HFT/MFT strategy. Quant Research Track Experience in developing machine learning algorithms, building automated pipelines for recalibration and testing, implementing version control systems, and visualising the training process. Nice to have requirements Experience in market making, including signal design and HFT strategy development. We are also open to candidates with experience in MFT strategies. Proven track record of winning global math, Kaggle, and programming competitions. High level understanding of C++. Deep understanding of Machine Learning. Here is why you should join our dynamic team Opportunity to work at one of the world’s leading algorithmic trading firms. Engaging projects offering accelerated responsibilities and ownership compared to traditional finance environments. A vibrant working culture with team meals, festive celebrations, gaming events and company wide team building events. A Wintermute‑inspired office in central London, featuring an array of amenities such as table tennis and foosball, personalised desk configurations, a cosy team breakout area with games. Great company culture: informal, non‑hierarchical, ambitious, highly professional with a startup vibe, collaborative and entrepreneurial. #J-18808-Ljbffr