Schonfeld
Hedge fund
QuantitativeDeveloper-FundamentalEquities
Neural analysis suggests this role is
optimal for Mid candidates.
“Quantitative Developer - Fundamental Equities at Schonfeld. Skills: Python, AI/LLM integration, Quantitative development, Dashboard building. Write clean, well-structured code. Contribute to engineering practices”
What You'll Achieve.
Improve productivity; Deepen AI adoption; Make better use of data; Drive AI integration; Deliver high-quality output; Create immediate value
Industry & Context.
Pragmatic solutions; Identify what needs to be built; Solve problems
What They're Looking For.
Must Have
2–5 years of experience in a relevant role, Python, solid SQL and database usage skills, Demonstrated experience building dashboards and UIs, Hands-on experience with AI/LLM integration, Practical familiarity with MCP servers, agentic frameworks, or multi-model orchestration architectures, Experience with AI-assisted development tools, Sound software engineering fundamentals, Actively engaged with the AI development landscape, Collaborative by nature, Product-minded, Comfortable in a business-facing team, Self-starter, Intellectually curious about financial markets and the investment process
Nice to Have
Exposure to alternative data ingestion or vendor API integrations, Prior experience in a hedge fund or multi-manager platform, Comfortable working within AWS, Experience with Docker, Kubernetes, and workflow orchestration frameworks
What You'll Do.
Contribute to engineering practices
maintain tools and dashboards
Surface quantitative outputs
Contribute to AI integration layer
Implement and operate AI capabilities
Work closely with quant researchers
Take analytical outputs to production
Identify where AI tooling can remove friction
How You'll Work.
Team & Collaboration
Work alongside quant researchers and COO management; Coordinate with central Technology teams; Share ideas openly; Contribute to collective knowledge; Work across technical and non-technical audiences; Work with investment professionals
Process & Methodology
Takes ownership end-to-end, Scoping, Delivery, Maintenance, Iteration
Full Job Description
The Role We are looking for a Quantitative Developer to join the Fundamental Equity COO team, embedded directly within the business rather than in a central technology function. You will work alongside quant researchers and COO management to build tools, dashboards, and data pipelines that improve productivity, deepen AI adoption, and make better use of the data the business already has access to. AI integration is a core part of this role, not an afterthought. We are actively building out how LLMs, agentic workflows, and AI-powered tooling fit into the investment process, and this hire is expected to drive a meaningful part of that. You should come in with both hands-on experience and genuine conviction about where these technologies are heading. The role sits close to the investment process. We are looking for someone proactive and delivery-focused: someone who identifies what needs to be built, takes ownership, and gets it done without waiting to be directed. The expectation is high-quality output, pragmatic solutions that work in the hands of investment professionals and create immediate value. What you’ll do Write clean, well-structured, maintainable code and contribute to good engineering practices within the team, including CI/CD pipelines and version control, with an active contribution to firmwide best practices so that deliverables can be broadly leveraged across the business Build, deploy, and maintain internal tools and dashboards that surface quantitative outputs, portfolio analytics, and market data in clean, intuitive interfaces, actively used by investment professionals Contribute to the AI integration layer in close coordination with central Technology teams: strategically implementing and operating AI capabilities tailored to the specific needs of the Fundamental Equity business, spanning LLM APIs, MCP servers, and agentic workflows, with the awareness that this is a rapidly evolving landscape requiring continuous reassessment of what best looks li
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