Trexquant Investment LP

About the Company

Trexquant is a leading quantitative finance firm specializing in the development of multi-asset portfolios through advanced machine learning methods. The firm continuously enhances its investment and research platform, utilizing a vast array of data variables to create complex trading models and strategies. These models generate trading signals aimed at outperforming market conditions globally.

Listed Jobs

Company Name

Trexquant Investment LP

Job Title

Data Scientist - Early Career (USA)

Job Description

**Job title:** Data Scientist – Early Career **Role Summary:** Focuses on a single asset class (equities, futures, bonds, options, or FX) to develop, test, and refine predictive models that drive trading strategies. Acts as the primary data expert for the chosen domain, collaborating across strategy, machine‑learning, and research teams. **Expectations:** - Deliver actionable data insights and predictive signals that enhance trading performance. - Own end‑to‑end data workflows: from data acquisition and cleaning to feature engineering and model deployment. - Maintain rigorous model validation, documentation, and compliance with firm standards. **Key Responsibilities:** - Partner with strategy and ML teams to identify profitable predictive signals and translate them into robust models. - Source, evaluate, and integrate new datasets from internal research or external vendors. - Conduct deep domain analysis of asset‑class data, attending conferences and working closely with data vendors. - Keep up with cutting‑edge data‑science and machine‑learning techniques relevant to quantitative finance. - Ensure reproducibility and maintain version-controlled pipelines for model training and evaluation. **Required Skills:** - Strong quantitative and analytical background with expertise in statistical modeling. - Proven experience developing and validating machine‑learning or econometric models. - Advanced proficiency in Python (NumPy, pandas, scikit‑learn, PyTorch/TensorFlow or equivalent). - Familiarity with data‑engineering tools (SQL, Airflow, Spark/Databricks, or similar). - Excellent problem‑solving abilities and clear communication of complex findings. **Required Education & Certifications:** - Bachelor’s, Master’s, or Ph.D. in Mathematics, Statistics, Computer Science, Quantitative Finance, or a related STEM field. - No explicit industry certifications required, but knowledge of financial data and regulatory frameworks is a plus.

Stamford, United states

Hybrid

02-11-2025