Systematic COO Intern
US$130,000 – US$145,000 / yr base salary
Posted 4 Sep 2026
Advertised as “2027 Systematic COO Intern”
BranchFactor Summary
The original posting with the fluff stripped out
- Management level
- Individual contributor
- Contract
- Internship
| Base salary | US$130,000 – US$145,000 / yr |
|---|
Field of studyComputer Science, Data Science, Engineering, Finance, Mathematics (or related)
Study levelBachelor's or higher
The Role
We are looking for a highly motivated Data & Business Analyst Intern to join Schonfeld’s Systematic Strategies COO (SCOO) team.
The Systematic business contains many separate investment (PM) teams. Schonfeld oversees these teams’ trading and risk, and supports them with capital, technology, execution, operations, legal, recruiting and general business services (aka the Platform). The SCOO team is the key interface between PM teams and these services.
Working within the SCOO team, you will build, enhance, and automate the tools and analytics used by our Platform to make faster data-driven decisions at scale.
This internship blends data, technology, and markets: you will gain exposure to systematic trading workflows, enterprise data architecture, AI/LLM development, and cross-functional project management while solving real operational challenges.
What You’ll Do
-
Investigate and integrate multiple enterprise data sources to build a unified analytics library for the SCOO team, handling diverse endpoints (PostgreSQL, REST APIs, Kafka streams)
-
Design and deploy AI-assisted data tools using agent skills and Python libraries that enable non-technical stakeholders to query complex data through natural language
-
Build production dashboards and automated reports (Power BI, Grafana, or HTML) that surface trading activity, vendor relationships, execution analytics, and operational KPIs
-
Automate manual processes including quarterly updates, onboarding tracking, expense reconciliation, and other tasks that require recurring data pulls using orchestration frameworks such as Prefect and Airflow
-
Collaborate across Technology, Risk, Operations, Reference Data, and Execution Services teams to understand data schemas, navigate access permissions, and validate data quality across systems
-
Create scripts and schemas for ad-hoc analyses (e.g., “How has average FX ticket size changed over time?”).
-
Document processes and proactively surface ideas to improve efficiency, data quality, and transparency across the Platform
What You’ll Bring
-
Currently pursuing a Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, Mathematics, Finance, or a related quantitative field (with ≤ 1 year left in your program).
-
Proficient in Python (Pandas, FastAPI/Flask, OOP) and SQL (query optimization, data modelling) - able to deliver rapid ad-hoc analyses and scale them into production-ready tools within the broader tech stack