The role involves collecting, cleaning, and structuring large datasets from various market and operational sources. The individual will develop and validate predictive models to support trading strategies while prototyping and refining data-driven trading ideas. Responsibilities include building and maintaining data pipelines, dashboards, and automated tooling to streamline workflows. The position requires utilizing LLMs and agentic frameworks to accelerate data analysis and automate cleaning processes. Furthermore, the role entails collaborating with traders, risk managers, and software engineers to integrate insights into real-time decision-making.

Candidates must hold a bachelor's or master's degree in Computer Science, Mathematics, Statistics, or a related field. Proficiency in Python, R, SQL, and data manipulation libraries like Pandas and NumPy is required. Applicants must demonstrate experience programmatically integrating LLMs into pipelines and building custom agents to interpret unstructured data. Fluency in English and a proactive, flexible work mentality are essential for the role.