Quant Developer (QD)

Quantitative Research & Development EngineerAlgert Global — San Francisco, CABuild alpha. Drive portfolios. Engineer the platform.Algert Global is a boutique investment firm applying data science and machine learning to global equity investing. Since 2003, we’ve partnered with some of the world’s most sophisticated institutional investors across market neutral, extension, and long-only strategies.At Algert Global our product is returns which means your work directly impacts portfolios, not just codebases. You’ll work side-by-side with experienced portfolio managers and investment professionals, learning how ideas translate into capital and performance in real markets.We’re looking for a high-agency, intellectually curious builder who wants to operate across the full stack of quantitative investing—from alpha research ↔ portfolio decisions ↔ systems and infrastructure.🚀 What You’ll DoThis role spans the full lifecycle of quantitative investing:📈 Alpha ResearchDevelop novel stock selection signals across :18,000 global equitiesOwn the full research pipeline: idea → data sourcing → cleaning → modeling → backtestingExplore alternative data, ML techniques, and new research workflows, we’re especially curious to see you build us an agentic research capablilityWork closely with PMs to translate ideas into deployable signals📊 Portfolio Management & Investment ProcessContribute to portfolio construction and monitoringEnsure research signals produce robust portfolio outcomesParticipate in rebalancing workflows and trade generationHelp maintain correctness, consistency, and explainability of the process⚙️ Research Platforms & SystemsBuild tools spanning:Research workflowsPortfolio analytics and attribution, including materials for client consumptionData pipelines and storage systemsImprove how portfolio managers and researchers interact with data, models, and results🖥️ Engineering, Infrastructure & WorkflowOptimize development workflows (Linux, IDEs, automation)Partner with engineers on CI/CD, DevOps, and system architectureDrive adoption of AI-assisted development and research toolingHelp shape infrastructure decisions across compute, storage, and databases🧠 What We’re Looking ForYou’re a builder + researcher + operator:4+ years of experience in Quantitative Investing shop (Citadel, Blackrock, pod shops, etc.)Strong interest in markets, trading, or investingAble to take ownership from idea → production → portfolio impactCurious, analytical, and philosophically mindedCollaborative but highly self-directedPragmatic: knows when to hack vs. when to engineer properly🤖 Why This Role Stands OutDirect link to P&L — your ideas and systems impact real capitalTrue full-stack quant role — research ↔ PM ↔ engineeringAI-native culture — help redefine how quant teams operateSmall team, high leverage — work directly with senior PMsMassive surface area — intellectual, technical, and financial growth💡 Who This Is ForThis is for someone early-to-mid career who wants:More ownership than large firmsMore breadth than siloed rolesMore impact than pure techIf you want to operate across alpha ↔ portfolios ↔ systems and see your work matter—this is that role.🛠️ TechnologiesWe use a modern, evolving stack. You don’t need everything—but you should recognize a lot of it and be excited to learn the rest.📈 Research & Data (alpha → portfolio)Python (pandas, numpy, scikit-learn, xgboost, statsmodels)SQL (MSSQL, Postgres)DuckDB, Arrow, Parquet (columnar analytics stack)Polars ↔ pandas (dataframe ecosystems)Jupyter / notebooks ↔ script-based research workflowsTime series analysis, cross-sectional modelingFeature engineering, signal pipelines, backtesting frameworks📊 Portfolio & Analytics (research PM)Portfolio construction tools (risk models, optimization, constraints)Factor models (e.g., Barra-style frameworks)Attribution systems, risk decompositionMarket data systems, pricing pipelinesSimulation frameworks, scenario analysis⚙️ Data Engineering & Platforms (research tech)ETL / ELT pipelines, Airflow / orchestrationData lakes & table formats (Parquet, Delta)Ibis ↔ SQL ↔ Python interoperability layersStreaming vs batch processing systems🖥️ Engineering & Infrastructure (tech → enabling everything)Python packaging, environments (uv, reproducibility tooling)Containers (Docker) ↔ orchestration (lightweight or K8s-style)CI/CD pipelines (Git-based workflows, automation)Infrastructure as Code (Terraform, Ansible)AWS (compute, storage, data services)APIs, microservices, backend systems🧠 AI-Augmented Development (cuts across everything)Claude Code, MCP, agentic workflowsAI-assisted research, coding, and data explorationBuilding internal tools that leverage LLMs for productivity🗄️ Databases & Storage (tech research)Microsoft SQL Server, Postgres, use required and management a plusSnapshotting, replication, backup strategiesObject storage, distributed storage systems🧰 Bonus / Nice to HaveProxmox, virtualization, cluster managementVeeam / backup systemsPure Storage / enterprise IBM storageLinux systems engineering🌉 LocationSan Francisco, CA — in-person collaboration required.⭐ U.S. Work Authorization RequiredYou must be authorized to work in the United States. We are not able to sponsor visas for this role.