Data and Business Analyst Intern
About The Position
We are looking for a highly motivated Data & Business Analyst Intern to join Schonfeld’s Fundamental Equity COO(FE-COO) team. You will partner closely with the FE-COO Team to strengthen our reporting and analytics infrastructure, automate key workflows, and help deliver intuitive dashboards for our Long/Short Fundamental Equity (L/S FE) investment teams. This internship blends technology and markets: you will code in Python & SQL, work with tools such as Power BI, Streamlit, and Prefect, and gain exposure to trading, risk, and portfolio analytics for global Long/Short equity strategies.
Requirements
- 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.
- Hands-on experience - or strong interest - in Power BI and/or Streamlit dashboard development.
- Strong analytical thinking, attention to detail, and the ability to communicate technical concepts to non-technical stakeholders.
- Comfort working autonomously in a fast-paced, global, highly collaborative environment.
Nice To Haves
- Knowledge of workflow orchestration tools (Prefect, Airflow, Dagster) a plus.
- Genuine curiosity about Long/Short Fundamental Equities, financial markets, and risk management; familiarity with the publicly traded earnings announcement life-cycle is advantageous.
Responsibilities
- Build and extend the Python-based FE-COO analytics library (data models, helpers, analytical toolkit, unit tests).
- Design & implement Power BI or Streamlit dashboards that visualize P&L drivers, risk metrics, and operational KPIs.
- Automate recurring reports and data pipelines (trade alerts, factor exposures, liquidity metrics) using Prefect (or similar orchestration frameworks) and CI/CD best practices.
- Collaborate with Risk, Technology, Operations, and Data Engineering teams to source, cleanse, validate and build analytical tools used by FE Portfolio Managers.
- Support PM and Analyst onboarding, new-strategy launches, and ad-hoc analyses (e.g., “How did the team perform through the Earnings window?”).
- Document processes and proactively surface ideas to improve efficiency, data quality, and transparency across the FE platform.
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What This Job Offers
Career Level
Intern
Number of Employees
501-1,000 employees
