QuantitativeDeveloper

ABOUT POESIS Whoever builds the leading intelligence for finance will create far more than returns. Poesis is the AI-native investment firm running autonomous agents that predict markets, construct portfolios, and manage risk. Our founders managed institutional capital at Capital Group ($3T AUM) and led enterprise ML at Goldman Sachs and Amazon. We're building a new type of firm, where live capital is the training ground for an intelligence that compounds with every signal. ABOUT THE ROLE We’re hiring a Quantitative Developer to help turn research ideas into production-grade code. You’ll help build data pipelines, implement models and ensure results are clean, reproducible and explainable. You’ll work alongside Poesis’ Chief Scientist, CEO and engineering leadership to turn large-scale data and quantitative research into models, signals and tools that drive investment decision-making. RESPONSIBILITIES - Rapidly implement and iterate on research ideas and model prototypes. - Clean, process, and join financial and fundamental datasets from professional and public sources. - Build and maintain processes for feature generation, back-testing, and model evaluation. - Run experiments, summarize results, and report findings to leadership. - Contribute to code quality: testing, documentation, and integration into shared systems. - Support the team in defining data schemas, APIs, and reproducibility standards. - Implement, test, and refine models, signals, and analytical workflows. - Maintain a consistent cadence of deliverables, focusing on iteration speed and reliability. REQUIRED COMPETENCIES - Strong Python skills (pandas, numpy, scipy, matplotlib); comfort with SQL. - Skill working with Claude Code, Codex, or other coding agents. - Proficiency working with real-world financial datasets and building reproducible analyses or pipelines. - Understanding of statistics, regression, optimization, and ML fundamentals. - Clear communicator who can explain technical findings to no