Senior Fund Accountant

Direct message the job poster from StreetID We are a dynamic and fast-paced hedge fund leveraging data-driven strategies to generate alpha in global financial markets. Our team of technologists, quantitative researchers, and portfolio managers work collaboratively to translate cutting-edge research into production-ready trading models and systems. We are seeking a highly motivated Quantitative Analyst/Developer to join our growing technology and research group. This role is ideal for candidates with a passion for data engineering, financial modeling, and software development. You will play a key role in building tools and frameworks that directly support quantitative research, strategy development, and live trading. Key Responsibilities: Design, develop, and maintain robust data pipelines to ingest, clean, and process large-scale financial datasets using Python, with an emphasis on the Pandas library for high-performance data manipulation. Collaborate with quantitative researchers to implement and optimize research tools, statistical models, and backtesting frameworks. Work on the development of analytics and visualization dashboards to support model performance analysis, trade monitoring, and risk reporting. Optimize and refactor existing codebases for efficiency, scalability, and maintainability, ensuring robust data integrity and reproducibility of research results. Write clean, well-tested, and production-ready Python code with a focus on numerical stability, performance, and low-latency data access. Integrate third-party financial data vendors and APIs (Bloomberg, Refinitiv, FactSet, etc.) into the research infrastructure. Support live trading and strategy deployment pipelines by ensuring smooth data flow and minimal downtime. Collaborate with DevOps and engineering teams to implement CI/CD pipelines, containerization (Docker), and cloud-based compute workflows where appropriate. Stay current with new technologies, libraries, and best practices in data science, financial engineering, and Python-based software development. Required Qualifications: Bachelor’s or Master’s degree in Computer Science, Applied Mathematics, Engineering, Physics, Statistics, or a related quantitative discipline. Experience in a quantitative developer, data engineer, or similar role, ideally within a hedge fund, trading firm, or financial institution. Extensive hands-on experience with the Pandas library for data manipulation, time-series analysis, and performance tuning. Strong proficiency in Python, with knowledge of its scientific computing stack (NumPy, SciPy, Matplotlib, Seaborn, etc.). Familiarity with software engineering principles: version control (Git), code reviews, testing frameworks, and continuous integration. Experience handling large, complex datasets and working with structured and unstructured data sources. Solid understanding of financial instruments (equities, derivatives, FX, fixed income) and market data. Excellent problem-solving skills, attention to detail, and the ability to work independently as well as in a collaborative team environment. Seniority level Seniority level Director Employment type Employment type Full-time Job function Job function Engineering and Information Technology Industries Investment Management, Financial Services, and Capital Markets Referrals increase your chances of interviewing at StreetID by 2x Sign in to set job alerts for “Quantitative Researcher” roles. 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