Quantitative Research Intern

Job Description

We are seeking a Quantitative Research Intern to support our efforts in market impact modeling, transaction cost analysis (TCA), and execution strategy optimization. This role is ideal for candidates with a strong background in applied mathematics, stochastic calculus, and quantitative finance, who are eager to contribute to the next generation of algorithmic execution solutions.

Key Responsibilities

1. Execution Research & Trade Cost Optimization:

• Develop data-driven models for measuring slippage, market impact, and execution efficiency.

• Apply causal inference techniques to assess the impact of different execution strategies.

• Conduct research on optimal execution models, including implementation shortfall and order placement strategies.

2. Quantitative Modeling & Machine Learning:

• Use advanced calculus, probability theory, and time-series modeling to improve execution performance.

• Implement machine learning models to predict trade cost, slippage, and order routing performance.

• Explore reinforcement learning and stochastic optimization for trade execution strategies.

3. Data Analysis & Research Implementation:

• Work with large-scale trading data to backtest execution models and evaluate performance.

• Translate academic research into practical execution strategies for minimizing transaction costs.

• Develop tools for real-time trade performance monitoring and TCA reporting.

Ideal Candidate Profile

1. Mathematical & Statistical Expertise:

• Strong foundation in calculus, stochastic processes, probability theory, and optimization.

• Experience with causal inference frameworks and econometrics in financial modeling.

2. Execution & Market Dynamics Knowledge:

• Understanding of trade execution strategies (VWAP, TWAP, IS), price impact models, and TCA.

• Familiarity with algorithmic execution frameworks and liquidity dynamics.

3. Programming & Data Analysis:

• Strong Python skills (NumPy, Pandas, SciPy, StatsModels, PyTorch, or TensorFlow).

• Experience handling large financial datasets and running data-driven experiments.

4. Research-Oriented Mindset:

• Capable of reading, synthesizing, and implementing findings from execution research papers.

• Ability to test, validate, and refine models using empirical data.

Why You Should Join Us

• Innovative Environment: Lead the charge in financial innovation at a company that's at the forefront of integrating advanced quantitative techniques with traditional financial models.

• Expert Team: Work alongside the brightest minds in an environment that values bold ideas and radical solutions to complex problems.

• Professional Growth: Enjoy a vibrant company culture that promotes career development, continuous learning, and work-life balance.

• Compensation: Receive equity-only compensation, recognizing your contributions to our success.

• Work Hours: This is a part-time role requiring 20-30 hours per week.

• Fast Paced Work: We are looking for candidates to start immediately; if you are searching for Summer roles, please contact us at a later date.

If you are passionate about leveraging mathematical models to drive financial innovation and eager to apply your quantitative skills to solve complex problems, join us. Together, we will chart the future of finance, today.