Quantitative Research Internship

Quantitative Research Intern – Execution Algorithms

Location: Remote or New York, NY (In-Person Preferred)
Company: Blockhouse
Job Type: Part-Time (25 - 30 hours/week)

About Blockhouse

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.

What You’ll Do

• 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.

What We’re Looking For

• 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.

Why Join Us?

• 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.

For International Students

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.