Quantitative Developer Resume Example

Quantitative Developer · Two Sigma

Chicago, IL · 2021 - Present

• Developed and optimized machine learning models for alpha signal generation across various asset classes, leading to a 15% improvement in strategy performance.
• Implemented high-frequency data processing pipelines in C++ and Python for tick data, reducing data latency by 200 milliseconds for real-time analytics.
• Collaborated with research teams to integrate novel deep learning techniques into existing quantitative strategies, enhancing predictive accuracy by 10% on key benchmarks.
• Built and maintained scalable distributed computing frameworks on AWS for backtesting and model training, supporting over 50 concurrent research projects.

Quantitative Analyst · Citadel

Chicago, IL · 2018 - 2021

• Designed and implemented quantitative strategies for options market making, resulting in a 7% increase in daily trading volume and profitability.
• Developed C++ libraries for low-latency pricing and risk management of complex derivatives, reducing calculation times by 30% for critical trades.
• Automated data ingestion and validation processes for tick data, improving data quality and reducing manual error rates by 90%.
• Contributed to the development of a real-time analytics platform using KDB+ for monitoring trading performance and market microstructure.

M.S. in Financial Mathematics · University of Chicago

Chicago, IL · 2017 - 2018

• Specialized in stochastic calculus, numerical methods for derivatives, and quantitative trading strategies.
• Thesis: "Machine Learning Approaches to Volatility Prediction in Equity Markets", achieving a GPA of 3.9/4.0.

B.S. in Computer Science · University of Illinois Urbana-Champaign

Urbana, IL · 2013 - 2017

• Concentration in Artificial Intelligence and Algorithms. Graduated with High Honors (Magna Cum Laude), GPA: 3.8/4.0.
• Coursework included advanced data structures, distributed systems, and statistical modeling.

Quantitative Developer · Citadel

Chicago, IL · 2022 - Present

• Optimized latency-sensitive trading strategies in C++ for high-frequency trading, reducing average trade execution time by 15ms.
• Designed and implemented new features for a proprietary market-making system, improving fill rates by 8% and increasing daily P&L by $250K.
• Developed robust data analysis tools in Python to monitor strategy performance and identify arbitrage opportunities across diverse asset classes.
• Collaborated with researchers to backtest and deploy new machine learning models, leading to a 3% improvement in signal strength for a core equity strategy.

Quantitative Developer · Optiver

Chicago, IL · 2020 - 2022

• Built and maintained low-latency trading infrastructure using Python and C++, supporting a volume of over 1 million trades per day.
• Developed quantitative models for volatility surface interpolation and option pricing, enhancing pricing accuracy by 12%.
• Streamlined data pipelines for market data ingestion and historical backtesting, reducing processing time for large datasets by 40%.
• Participated in a team that deployed an automated execution algorithm, generating an additional $1.5M in annual revenue.

Data Scientist/Consultant · Accenture

Chicago, IL · 2018 - 2020

• Led client engagements to develop and implement machine learning solutions for operational efficiency, resulting in an average cost reduction of 10% for key projects.
• Designed and executed A/B tests for digital marketing campaigns, improving conversion rates for a major retail client by 7%.
• Developed predictive models using Python (scikit-learn, TensorFlow) and R to forecast consumer behavior, achieving 90% accuracy.
• Presented complex analytical findings to C-suite executives, guiding data driven strategic decisions for Fortune 500 companies.

M.S. in Financial Mathematics · University of Chicago

Chicago, IL · 2018 - 2020

• Specialized in stochastic calculus, numerical methods for finance, and quantitative risk management.
• Developed a Monte Carlo simulation model for exotic option pricing with C++ and Python.
• Coursework included High Performance Computing, Machine Learning in Finance, and Time Series Analysis.

B.S. in Applied Mathematics, Summa Cum Laude · University of Illinois Urbana-Champaign

Champaign, IL · 2014 - 2018

• GPA: 3.9/4.0, awarded departmental honors for outstanding academic achievement.
• Completed a senior thesis on predictive modeling using advanced statistical techniques.
• Relevant coursework: Probability Theory, Statistical Inference, Differential Equations, Linear Algebra, Object Oriented Programming.