Senior Quant Developer - Python/Data (M/F)

Future Role

• Collaborate with quant researchers and data engineering teams to develop quantitative tools for trading and research (e.g., creating ETL pipelines to integrate and test alternative datasets for the commodities desk).
• Design and implement machine learning/statistical models for systematic commodity trading.
• Perform data exploration and strategy backtesting.
• Maintain, support, debug, and enhance existing commodities trading and research infrastructure alongside researchers and support engineers.
• Work with the AWS infrastructure team to architect, develop, deploy, and manage cloud-native applications (e.g., systems for storing and exploring alternative datasets, risk reports, and PnL).

Present Skillset

• At least 5 years of experience in front office quant development.
• Expertise in Python, particularly with numerical libraries such as NumPy, pandas, and matplotlib.
• Strong quantitative skills and financial knowledge.
• Proficient in AWS (or a similar cloud platform) and infrastructure-as-code (IaC).
• Skilled in databases (e.g., SQL).
• Familiar with development practices including version control with Git, unit testing, and packaging.
• Team-oriented with a collaborative mindset.

Nice to Have

• Experience in commodities trading, especially in the energy sector.
• Background in modeling and backtesting.
• Advanced AWS experience (e.g., DynamoDB, RDS, S3, Lambda, AWS CDK).
• Deep knowledge of databases (e.g., query optimization, understanding relational vs non-relational databases).
• Experience with parallel computation and distributed computing.