Key Responsibilities:

📍Collaborate with quantitative researchers to understand their workflow, challenges, and requirements, and provide technical solutions to improve their research productivity 📍Design, develop, and maintain software tools, platforms, and frameworks that enhance the efficiency and effectiveness of research activities, including data gathering, preprocessing, analysis, and model development 📍Identify and implement advanced data processing techniques, algorithms, and statistical methods to optimize research workflows and enhance data analysis capabilities 📍Leverage your expertise in software engineering, data engineering, and machine learning to build scalable and robust systems that facilitate large-scale data analysis and experimentation 📍Conduct code reviews, provide technical guidance, and mentor junior research engineers to ensure code quality, maintainability, and adherence to best practices 📍Collaborate with cross-functional teams, including quantitative researchers, data scientists, and engineering professionals, to integrate research tools and systems into the existing infrastructure 📍Assist in the evaluation and implementation of third-party tools, libraries, and data sources that can enhance the research process 📍Participate in research discussions, contribute ideas, and provide technical expertise to improve research methodologies and strategies 📍Contribute to the development and maintenance of documentation, user guides, and training materials related to research tools and processes

Skill Set and Qualifications:

📍4+ years experience working in close partnership with quantitative researchers to develop, deploy and maintain quantitatively-driven alpha strategies. Previous experience at a quantitative hedge fund is strongly preferred. 📍Master's or Ph.D. in Computer Science, Engineering, Data Science, or a related field 📍Exceptional Python programming skills, with a focus on building scalable and efficient systems, embracing best-in-class open source data science tooling. 📍Proficiency in data processing, analysis, and visualization tools, libraries, and frameworks 📍Solid understanding of statistical modeling, machine learning techniques, and their practical applications in quantitative research 📍Solid understanding of the differences between L1, L2 and L3 market tick data 📍Experience with AWS 📍Excellent problem-solving skills and the ability to design practical solutions to complex research challenges 📍Strong communication and collaboration skills to effectively work with cross-functional teams and translate research requirements into technical solutions