Quantitative investment manager building trading and portfolio analytics systems
Two Sigma is a quantitative investment firm running Python, C++, Java, and a heavy ML stack (PyTorch, TensorFlow, scikit-learn, JAX) across ~1,700 employees. Active migration to cloud-native infrastructure (AWS, Azure, GCP, Kubernetes) and adoption of FPGAs suggest a shift toward lower-latency execution and real-time feature computation. Engineering-heavy hiring (17 roles) combined with active research teams (9 roles) and projects around low-latency frameworks and model productionalization indicate scaling bottlenecks in trading systems and research-to-production workflows.
Two Sigma is a financial services firm focused on investment management, trading, and portfolio analytics. The company builds quantitative trading systems and investment models across global markets, serving clients in securities, private equity, real estate, venture capital, and insurance. With headquarters in New York and offices internationally (including active hiring in the UK), the firm operates mission-critical trading and data infrastructure. Current work centers on expanding asset class coverage, productionalizing research insights, and improving the reliability and latency of trading and forecasting systems.
Two Sigma's core stack includes Python, C, C++, Java, NumPy, SciPy, PyTorch, TensorFlow, scikit-learn, and JAX for quantitative modeling. Infrastructure runs on AWS, Azure, and GCP with Kubernetes and Docker for orchestration. The firm recently began adopting FPGAs, likely for low-latency trading systems.
Two Sigma is actively hiring in the United Kingdom in addition to its New York headquarters. The company employs over 1,700 people across global offices.
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