Quantitative Developer

Responsibilities

• Build and maintain derived datasets and data products for quantitative research and strategy work
• Source, capture, and curate market data from various exchange formats, including multicast/UDP feeds
• Develop and deploy analytical tools and data pipelines for both research and production environments
• Manage large-scale backtest compute on distributed clusters
• Own data quality and incident response by investigating and resolving data anomalies or delays
• Performance-tune storage and processing to improve data layout, load times, and throughput

Requirements

• Strong proficiency in Python, specifically the data stack (NumPy, Pandas, and Polars)
• Experience with large-scale data storage formats such as HDF5 or Parquet
• Experience processing large and varied datasets
• Comfortable working in a Linux environment
• Solid understanding of computer networking
• Ability to understand financial data, models, and mathematical algorithms
• Strong interpersonal and communication skills for collaborating with traders and researchers

Preferred Qualifications

• Experience or interest in capital markets and market data
• Knowledge of probability and applying engineering solutions to financial problems

Benefits

• Real impact by optimizing systems that process massive amounts of data
• High level of collaboration with Trading, Quantitative Research, and Infrastructure teams
• Opportunities for continuous innovation and professional growth
• Competitive employee perks and benefits

About the Company

Susquehanna is a global quantitative trading firm powered by scientific rigor, curiosity, and innovation. We specialize in trading a wide range of financial products, with a focus on derivatives, using advanced quantitative research and machine learning to uncover actionable insights in global markets.