Quantitative Developer - Systematic

The Role

We're setting up a new engineering team in Shanghai, working hand-in-hand with Portfolio Managers to develop and deploy new systematic trading strategies. As a Software Engineer in the Front-Office Engineering organization, your code will have a direct line of sight to live markets.

Your work will span the full lifecycle of strategy development: onboarding new datasets, implementing trading signals, building portfolio optimization tools, developing data visualization frameworks, and enhancing our research platform. You'll solve performance-critical problems using efficient numerical algorithms and cluster-computing solutions.

This is a chance to get in early and do engineering work that visibly moves the needle.

Our Technology

Our systems are almost all running on Linux and most of our code is in Python, with the full scientific stack: NumPy, SciPy, Pandas, statsmodels, and scikit-learn to name a few of the libraries we use extensively. For storage, we rely heavily on MongoDB and MS SQL. 

We use Control-M and Airflow for workflow management, Kafka for data pipelines, Bitbucket for source control, Jenkins for continuous integration, Grafana + Prometheus for metrics collection, Docker for containerisation, Ansible for architecture automation, and Slack for internal communication. Our technology list is never static: we constantly evaluate new tools and libraries.

Key Competencies 

Essential

• Minimum of 2 years of professional experience in software engineering, preferably with a focus on quantitative applications
• Proficiency in Python and experience with scientific libraries including Pandas, NumPy, SciPy, stats models and scikit-learn
• Experience working on production systems, with an understanding of best practices for testing, monitoring, and deployment
• Comfortable working on Linux platforms and using Git
• Working knowledge of one or more relevant database technologies, such as MS SQL, Postgres, or MongoDB

Advantageous

• Experience in quantitative software development within a front-office setting, such as at a hedge fund, proprietary trading firm, or investment bank
• Experience working with large data sets, both structured and unstructured
• Experience building web applications using modern frameworks like React
• Proficient with distributed computing technologies such as Spark, Dask, Kubernetes, Redis
• Knowledge of modern data engineering practices including data pipeline & ETL tools, distributed storage & processing and data warehousing
• Strong understanding of financial markets and instruments
• Experience working with financial market data
• Relevant mathematical knowledge e.g., statistics, time-series analysis

Working Here

Man Group established its Shanghai presence in 2012 and was among the first global alternative managers to secure a Private Fund Manager license in China (2017), giving you a front-row seat at one of the industry's most significant market-access stories. 

Our Shanghai team is made up of quant researchers, developers and portfolio managers. We operates with genuine start-up energy inside a major global firm: you will build greenfield technology and research infrastructure for Chinese markets, working directly alongside colleagues in London, Boston and Sofia. The work spans AI/ML-driven alpha research, high-performance Python systems, alternative data pipelines and trading signal implementation — all backed by Man's global compute platform and open-source tools like ArcticDB.