Varsity Holdings – Systematic Quant Trader Intern (US Equities / Intraday)

Role Overview

We are looking for a Systematic Quant Trader Intern with prior experience in quantitative research or systematic trading.

This is not a beginner role — you are expected to already understand how systematic strategies are built, tested, and deployed.

You will work directly on alpha research, feature engineering, and strategy validation using real market data.

What You’ll Do

• Design and test systematic trading strategies (long/short, intraday focus)
• Generate quantifiable features from price, volume, and market structure data
• Analyze large trade logs to identify high-EV patterns and failure modes
• Conduct event-driven backtests with realistic assumptions (slippage, liquidity, latency)
• Build and refine entry/exit logic, filters, and risk rules
• Perform multi-factor and interaction analysis (non-linear relationships, regime dependency)
• Contribute to improving our research pipeline and tooling

Requirements (Strict)

• Prior experience in:
  • Quantitative research OR
  • Systematic trading (personal or professional)
• Strong understanding of:
  • Backtesting principles (look-ahead bias, survivorship bias, overfitting)
  • Market microstructure basics
  • Statistical thinking (not just running indicators blindly)
• Experience working with:
  • Python (pandas, numpy) or equivalent
  • Large datasets / time-series data
• Ability to think in rules, conditions, and edge — not opinions

Preferred (High Signal)

• Experience trading small/mid-cap US equities
• Familiarity with:
  • Intraday data (1-min / tick)
  • Feature engineering for trading systems
  • Event-based strategy design
• Experience with:
  • C++, ClickHouse, or high-performance systems
• Built your own:
  • Backtester, trading bot, or research framework

What We Care About (Read Carefully)

• You’ve actually built and tested strategies, not just learned theory
• You understand that:
  • Most edges are context-dependent
  • Simple ideas break under realistic assumptions
• You can explain:
  • Why a strategy works
  • When it stops working
• You are comfortable being wrong often and iterating fast

What You’ll Get

• Direct exposure to live systematic trading strategies
• Work on real alpha generation, not toy problems
• Access to high-quality market data and infrastructure
• Opportunity to convert to full-time based on performance

How to Apply

Send:

• Your resume
• A brief write-up of 1–2 strategies you’ve built/tested
  • Include logic, edge hypothesis, and results
• (Optional but strong signal) GitHub / research notes / trade logs

If you don’t have prior systematic trading or QR experience, this role is not for you.