Quantitative Researcher - Data Curation

<p>We are seeking a highly analytical and detail-oriented <strong>Quantitative Researcher</strong> to join our dynamic research team. The ideal candidate will have deep experience curating and analyzing a broad range of trading-related data sources—including traditional market data, fundamental datasets, and other vendor-supplied information. This role will contribute to the development of innovative trading strategies, support data-driven decision-making, and collaborate closely with trading, technology, and data acquisition teams.</p> <p><strong>Key Responsibilities:</strong></p> <ul> <li>Curate, cleanse, and validate large volumes of market data, focusing on US equity and equity options</li> <li>Integrate, preprocess, and evaluate fundamental & alternative data sources</li> <li>Work closely with data acquisition & global data team to assess data quality</li> <li>Build and maintain robust data pipelines for research and live trading environments</li> <li>Perform data analysis ad statistical modeling to identify patterns and inefficiencies in the market</li> <li>Ensure the accuracy, completeness, and timeliness of datasets used in quantitative modeling.</li> <li>Document research processes, data provenance, and results with high standards of clarity and reproducibility</li> <li>Collaborate with software engineers and traders to translate research into production-grade models and tools</li> <li>Conduct quantitative research and analysis to support and enhance trading strategies<strong> </strong></li> </ul> <p><strong>Required Skills & Experience:</strong></p> <ul> <li>3+ years of experience in a quantitative research or data-focused role in financial markets, ideally in a systematic trading environment</li> <li>Proven experience working with a diverse range of trading and financial data</li> <li>Must have previous knowledge of options markets and experience working with options data</li> <li>Hands-on experience integrating and analyzing non-market data sources is a plus</li> <li>Strong understanding of data vendor landscape</li> <li>Advanced proficiency in Python</li> <li>Experience with databases (SQL) and handling large datasets efficiently</li> <li>Familiarity with real-time data systems and tick-level data processing</li> <li>Familiarity with statistical and machine learning techniques</li> <li>Exceptional attention to detail and a systematic approach to problem-solving</li> <li>Strong written and verbal communication skills</li> </ul> <p><span style="color: rgb(221, 234, 255);">#LI-DNP</span></p><div class="content-pay-transpa