Location: Remote or New York, NY (In-Person Preferred)
Company: Blockhouse
Job Type: Part-Time (25 - 30 hours/week)
Blockhouse is building intelligent execution algorithms for institutional traders. Our platform leverages advanced market microstructure modeling, machine learning, and real-time signal generation to minimize slippage and improve execution quality across equities and fixed income markets.
We’re looking for a Quantitative Research Intern who’s excited to work on hard problems at the intersection of optimization, statistical inference, and trading execution. This is a hands-on research and engineering role with exposure to our core production algos and trading infrastructure.
Engineer and validate high-quality execution signals such as order flow imbalance (OFI) and cross-impact features at multiple depths of the order book.
Apply causal inference techniques to evaluate the predictive power of features across market regimes.
Use Python to construct research pipelines for feature analysis, backtesting, and strategy simulation.
Collaborate with senior researchers to evaluate algorithm performance against benchmarks like TWAP and VWAP, with a focus on volatility and execution timing.
Contribute to internal research documentation and model version tracking.
Currently pursuing or recently completed a Bachelor’s or Master’s degree in Applied Math, Computer Science, Statistics, Financial Engineering, or related field.
Strong proficiency in Python, including libraries for numerical computing, optimization, and data visualization (e.g., NumPy, Pandas, Scikit-learn, Matplotlib).
Experience implementing mathematical models from papers and articulating objective functions, input parameters, and constraints.
Understanding of order book dynamics, basic execution benchmarks, and signal-to-noise challenges in financial data.
Prior exposure to causal inference, feature engineering, or real-time systems is a plus but not required.
Ability to work independently, communicate clearly, and ask the right technical questions.
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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