Python Developer- Quant Core Data

• Build and maintain backtesting systems that simulate strategy behavior in production
• Design and scale our historical data framework for efficiency and robustness
• Build internal tools to create, analyze, and visualize large datasets
• Build packages used by expert researchers to evolve our signal generation technology

• PhD (graduating by Summer 2026) or postdoc in a quantitative field (e.g., Math, Physics, Statistics, EE, CS, Operations Research, Economics)
• Experience writing high-performance Python (Cython, pybind11, numba, or similar) and optimizing hot code paths
• Strong Python data analysis skills (polars/pandas) for large datasets
• Enthusiasm for data at scale, with strong attention to cleanliness and correctness
• Comfort translating ambiguous research requirements into robust engineering solutions

Susquehanna is a global quantitative trading firm powered by scientific rigor, curiosity, and innovation. Our culture is intellectually driven and highly collaborative, bringing together researchers, engineers, and traders to design and deploy impactful strategies in our systematic trading environment. To meet the unique challenges of global markets, Susquehanna applies machine learning and advanced quantitative research to vast datasets in order to uncover actionable insights and build effective strategies. By uniting deep market expertise with cutting-edge technology, we excel in solving complex problems and pushing boundaries together. What we do We are experts in trading essentially all listed financial products and asset classes, with a focus on derivatives trading. Through market making and market taking, we handle millions of trading transactions around the world every day, providing liquidity and ensuring competitive prices for buyers and sellers. While our presence in the market is broad, our trading desks are highly specialized, allowing for a deep understanding of unique drivers of each asset class.