Quantitative Developer

You will work closely with a lean team of our portfolio manager and quantitative researcher team to design, build, and maintain the systems that power our quantitative investment process. This role sits at the intersection of quantitative research, software engineering, and trading operations. You will help turn research ideas into robust, production-ready systems and shape the technical foundation of the firm. You will also contribute to the evaluation, implementation, and scaling of machine learning and AI-driven approaches that have contributed to alpha, spanning research workflows, data pipelines, and internal tools, in collaboration with other teams at the firm. Key Responsibilities: Your work will directly impact fund performance and risk resilience. Your key responsibilities will be to: Design and enhance our current systematic research and trading infrastructure Implement and maintain backtesting frameworks and research pipelines Productionize quantitative strategies and support live trading systems Work with large financial datasets (market data, fundamentals, alternative data) Optimize performance, reliability, and scalability of research code Build tools for data ingestion, cleaning, normalization, and storage Collaborate closely with PMs on model implementation and iteration Assist with monitoring, debugging, and improving live strategies Support the integration of machine learning techniques into quantitative research, feature engineering, and signal development Support the building and maintenance of AI-enabled research and productivity tools (e.g., model experimentation, data analysis, internal tooling) Required Qualifications: 7+ years of experience working in a backend role 3+ years of experience working as a lead in a technical team 5+ years of experience working with Python Solid understanding of data structures, algorithms, and software design Experience working with financial market data and time series Familiarity with quantitative research workflows and backtesting Experience building or maintaining production systems Ability to work independently and make sound technical decisions Ability to work collaboratively with quantitative researchers and developers Familiarity with machine learning methods (e.g., regression, tree-based models, neural networks) and their application to financial data Preferred / Nice to Have: 3+ years of experience in a hedge fund, prop trading firm, or quantitative asset manager 3+ years of exposure to systematic trading strategies (equities, futures, FX, or crypto) 3+ years of experience working as a technical lead Experience with performance optimization (vectorization, multiprocessing, etc.) Knowledge of SQL, cloud infrastructure (GCP/AWS), or distributed systems Understanding of portfolio construction, risk, or execution systems Background in math, statistics, physics, or engineering What Makes This Role Unique: Technical hire joining an early hedge fund team with the ability to have significant ownership and influence Direct collaboration with decision-makers (PMs and leadership) Opportunity to shape architecture, tools, and best practices Exposure to the full lifecycle: research → production → trading Opportunity to work on applied AI initiatives and collaborate across the firm on AI-driven research and engineering efforts, alongside core quantitative trading systems. Competitive compensation with strong upside for the right candidate #J-18808-Ljbffr One Concern