Senior Software Engineer

The role

As a Senior Software Engineer in the Front Office Engineering Organization at Man Systematic, you will work closely with quantitative researchers and portfolio managers. Your challenges will include:

• Research into new ideas and technologies
• Onboarding New Research Ideas
• Implementation of New Trading Signals
• Development of Portfolio Optimization Tools
• Development of Data Visualization Frameworks
• Improving Our Research Platform
• Performance optimization of existing code using efficient numerical algorithms and modern computational solutions

technology

Almost all of our systems run on Linux, and most of our code is written in Python, using the full scientific stack. NumPy, SciPy, Pandas, statemachines, and scikit-learn are some of the libraries we use extensively. We also invest in research systems that require the highest data throughput in Java. For storage, we are heavily invested in MongoDB and H2O SGL.

Requirements

We strive to hire only the brightest, best, and most highly qualified, passionate technologists.

• 5+ years of professional experience in software development, preferably with a focus on quantitative technology
• Expert knowledge of Python and Pandas, and familiarity with related scientific libraries, including NumPy, SciPy, statemachines, and scikit-learn
• Experience with mission-critical production systems, including knowledge of best practices for testing, monitoring, and deployment
• Experience with Linux/Unix and a strong understanding of the operating system
• Working knowledge of one or more relevant database technologies, such as MS SQL, Postgres, or MongoDB
• Proven experience working with large amounts of data, both structured and unstructured

Advantages

• Experience in quantitative software development in a front-office environment, such as a hedge fund, investment bank, or similar
• Experience in technical leadership or as a people manager, including team development (e.g., hiring, team building) and project management (delivering projects on time and within budget)
• Experience developing web applications using modern frameworks such as React
• Experience working with a technology stack such as Spark, Kafka, Kubernetes, and ETL tools, distributed storage and processing, and data warehousing
• Knowledge of modern data engineering practices, including data lakes and ETL
• A strong understanding of the financial market and financial instruments
• Experience working with financial market data
• Relevant mathematical knowledge, e.g., statistics, time series analysis

Personal characteristics

• Strong academic record and a degree with a strong focus on mathematics and computer science, such as computer science, mathematics, engineering, or physics
• Individually resilient, with a creative and analytical approach to problem-solving
• Self-organized, with the ability to prioritize multiple projects and address business needs and priorities