Python Software Engineer - Digital Assets

IMC has a strong presence in traditional Finance and has been expanding into Crypto over the last years. Through its overseas affiliates, IMC provides liquidity and trades on many cryptocurrency exchanges and DeFi protocols. You can expect a dynamic, fast-paced environment that delivers a steady stream of challenges and opportunities, with one of the most exciting aspects of the job being our quick feedback loop in the research, development and deployment of strategies. As a Python Software Engineer, you will work closely with our trading and engineering teams on a variety of applications, tools and automation projects. You’ll be placed in an environment consisting primarily of a large Python analysis ecosystem drawing data from various sources including our own trading systems. You’ll build analysis & visualisation tools at the heart of the business logic, in close collaboration with the traders who use them. Your work involves both interpreting ideas, coming up with your own, and efficiently implementing these into tools that are reliable, scalable and performant. Together with traders, researchers and engineers, you deliver challenging projects, while taking ownership for end-to-end product development – from requirements gathering to production. You’ll write reliable and scalable software while balancing time to production with quality and testability. Advanced automated testing and daily deployments will allow you to achieve agile and incremental benefits. Within a complex landscape of varying systems and technologies, you’ll be constantly challenged to consider trade-offs between throughput, simplicity, scalability and maintainability.   Your Core Responsibilities:  Collaborate closely with researchers, and engineers to deliver challenging projects. Build, maintain, and enhance research frameworks and data pipelines that enable trading and quantitative research. Curate, transform, and present data in clear, accessible formats for traders and researchers. Take ownership of end-to-end product development, from requirements gathering to production deployment Navigate a complex landscape of diverse systems and technologies, making informed trade-offs between throughput, simplicity, scalability, and maintainability   Your Skills and Experience: Master’s or Ph.D. in Mathematics, Physics, Statistics, Computer Science, Econometrics, or a related discipline. 2–3 years of professional Python development experience solid computer science knowledge, has experience or capability to quickly adapt to additional languages such as Java, Scala, C++, Go, etc. Hands-on experience with statistical analysis, numerical programming, data engineering, or machine learning in Python (Polars, Pandas, NumPy, SciPy, TensorFlow). Proven ability to handle large datasets, architect and optimize data pipelines, and present data effectively. Experience with orchestration and containerization tools like Kubernetes and Docker is a plus. Solid grounding in calculus, probability, statistics, and optimization; familiarity with machine-learning techniques is beneficial.   Location and Office Culture: IMC office in Zug, Switzerland Note that this is an onsite role, with some but limited flexibility for working from home You can expect a dynamic, fast-paced environment that delivers a steady stream of challenges and opportunities One of the most exciting aspects of the job is our quick feedback loop in the research, development and deployment of strategies We give people lots of responsibility and the support they need to make an impact from day one We promise you a flat structure and an open, collaborative culture that stimulates the sharing of ideas, knowledge and technology between our teams and offices About Us IMC is a research-driven trading firm where quantitative modeling, machine learning, and engineering shape how modern markets are traded. A stabilizing force in markets since 1989, we provide liquidity across trading venues, delivering the best outcome in value and risk management to investors. Using our own technology and capital, we build proprietary systems and algorithms that operate across global markets. Our researchers, traders, and engineers work as a collective, combining rapid experimentation, advanced infrastructure, and real-time feedback to turn insight into execution and execution into advantage.  

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