Location: Remote or New York, NY (In-Person Preferred)
Company: Blockhouse
Job Type: Part-Time (25 - 30 hours/week)
Blockhouse is building cutting-edge execution algorithms that help institutional trading desks minimize slippage and optimize trade routing in real-time. Our flagship product is a smart order routing algorithm designed for volatile and fragmented markets across equities and fixed income. We combine research-grade modeling with practical deployment to deliver robust performance at scale.
We are seeking a Quant Strategist Intern to help prototype and evaluate new smart order routing strategies using high-frequency quote data and parameterized cost models. You’ll work directly on models that simulate live market interactions and drive meaningful performance improvements in execution quality.
Evaluate routing algorithm parameters (e.g., queue penalty, adverse selection cost, overfill/underfill weights) using mocked Level 1 market data.
Design a structured backtest over quote data to simulate execution, track fills, and calculate implementation costs.
Compare routing logic performance against baseline benchmarks (TWAP, VWAP, naïve best ask) to quantify cost savings and fill efficiency.
Report results using clean JSON summaries and modular, reproducible Python code.
Reflect on potential improvements to the fill simulation and broader real-world routing challenges.
Currently pursuing or recently completed a Bachelor’s or Master’s degree in Computer Science, Statistics, Financial Engineering, Applied Math, or a related field.
Strong proficiency in Python (especially Pandas and NumPy); clean, modular scripting is a must.
Experience with backtesting, simulation logic, or evaluating model performance.
Understanding of execution algorithms, queue dynamics, and order book microstructure is preferred but not required.
Clear thinking about model performance tradeoffs (cost vs. fill quality) and ability to reason from data.
Ability to document thought process clearly and write production-quality research code.
Work directly on algorithms that impact real-world trade execution.
Learn from senior quant researchers and gain experience translating academic research into production-quality systems.
Fast-paced, intellectually rigorous environment with ownership from day one.
Fully remote-friendly with optional in-person work in NYC.
Compensation: Mixture of cash and equity-based compensation, depending on experience and hours committed.
Blockhouse supports CPT/OPT, is e-verified, and accommodates flexible international payment arrangements.
If you're interested, we encourage you to submit your resume directly on this platform. We look forward to hearing from you.
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