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 like
• Work closely with quant researchers to take analytical outputs from prototype to reliable, production-ready applications
• Continuously identify where AI tooling can remove friction, improve output quality, or unlock capabilities the team does not currently have

What you’ll bring

What you need:

• 2–5 years of experience in a relevant role: quantitative development, dev strats, analytics engineering, product management, or quantitative analysis at a bank, hedge fund, asset manager, or financial data provider
• Strong Python proficiency; solid SQL and database usage skills (relational and/or time-series)
• Demonstrated experience building dashboards and UIs that were actively leveraged by investment teams or professional users in a production environment
• Hands-on experience with AI/LLM integration: API usage, prompt engineering, tool use, and retrieval-augmented workflows. You have built things with these, not just read about them
• Practical familiarity with MCP servers, agentic frameworks, or multi-model orchestration architectures (custom implementations or equivalent)
• Experience with AI-assisted development tools (e.g. Claude Code, Cursor, or similar) as part of a day-to-day engineering workflow
• Sound software engineering fundamentals: version control, structured codebases, CI/CD pipelines, documentation, testing
• Actively engaged with the AI development landscape: you follow what is changing, test new tools and frameworks hands-on to form your own views, and translate those views into practical decisions about what to build and how
• Collaborative by nature: you share ideas openly, contribute to collective knowledge, and are comfortable working across technical and non-technical audiences, from quant researchers and central Tech teams to investment professionals. The team culture is open, engaged, and friendly, and we are looking for someone who genuinely thrives in that environment
• Product-minded: you think about who is using the tool and what problem it solves, not just whether the code runs
• Comfortable in a business-facing team where pace matters and requirements evolve. This is not a research lab environment
• Self-starter who takes ownership end-to-end, from scoping and delivery through to maintenance and iteration
• Intellectually curious about financial markets and the investment process

We’d love if you had:

• Exposure to alternative data ingestion or vendor API integrations
• Prior experience in a hedge fund or multi-manager platform
• Comfortable working within AWS: EC2, containerized workloads, and infrastructure managed via Terraform or similar IaC tooling
• Experience with Docker, Kubernetes, and workflow orchestration frameworks (Prefect, Airflow, or equivalent)

Who we are
Schonfeld is a global multi-manager hedge fund that strives to deliver industry-leading risk-adjusted returns for our investors. We leverage both internal and external portfolio manager teams around the world, seeking to capitalize on inefficiencies and opportunities within the markets. We draw from decades of experience and a significant investment in proprietary technology, infrastructure and risk analytics to invest across four main strategies: Quant, Tactical, Fundamental Equity and Discretionary Macro & Fixed Income.

Our Culture
At Schonfeld, we’ll invest in you. Attracting and retaining top talent is at the heart of what we do, because we believe that exceptional outcomes begin with exceptional people. We foster a culture where talent is empowered to continually learn, innovate and pursue ambitious goals. We are teamwork-oriented, collaborative and encourage ideas—at all levels—to be shared. As an organization committed to investing in our people, we provide learning and educational offerings and opportunities to make an impact. We encourage community through internal networks, external partnerships and service initiatives that promote inclusion and purpose beyond the firm’s walls.