Tianyi Chen
Chicago
Summary
Highly-motivated employee with desire to take on new challenges. Solid experience in the competitive market of high frequency trading, strong technical background and mental aptitude for competing in the most demanding environment.Strong work ethic, adaptability, and exceptional interpersonal skills.
Overview
4
4
years of professional experience
Work History
Quantitative Trader
IMC Chicago
Chicago
08.2023 - Current
- Led initiatives to enhance SPX options quoting through CBOE exchange microstructure analysis and design of competitive price-time quoting algorithm.
- Analyzed, maintained, and enhanced global automated options trading system, improving performance robustness.
- Developed expertise in U.S. OCC options ecosystem, emphasizing liquidity provision in SPY index options and relevant PFOF business
- Conducted research on ES futures valuation in high-frequency trading, identifying inefficiencies and proposing enhancement opportunities.
Quantitative Trader Intern
IMC Financial Markets
Chicago
06.2022 - 08.2022
- Designed an algorithm using Python to automatically identify and classify a certain type of trades by competitors among 4 million rows of data per day, while achieving high precision and recall
- Analyzed patterns across 2000 examples using Pandas, summarizing actionable improvements for IMC's system, including latency requirements and smart execution mechanism selection
- Completed training in trading landscape, basic option theory, and technical analysis while designing a fully automated trading bot that generated $1000+ in final competition
Education
Bachelor of Science - Computer Science, Computer Systems, Algorithms & Complexity, Mathematical Sciences
Carnegie Mellon University
Pittsburgh, PA05-2023
Skills
- Automated trading
- Options pricing
- Algorithm design
- Risk management
- Data analysis
- Python/C/Java/SQL
- Research/machine learning
- Team collaboration
Projects
- Parallel Computing (CUDA, OpenMP, MPl), 09/22, Designed and implemented 2 parallel algorithms for Delaunay Triangulation useful for terrain simulation and mesh generation, achieving super linear speedup on 128-core supercomputer., Implemented scientific computing problems, such as n-body simulation, using 2 different parallel programming models - OpenMP and MPl, achieving nearly 100x speed on 128 processors.
- Distributed System (C, Java), 03/22, Implemented distributed file system supporting standard C file operations using RPC to achieve transparent local access of remote resource, refined by adding a concurrent caching proxy that preserves open-close session semantics, achieved cache consistency and robustness with check-on-use and LRU eviction policy., Built a multi-tier web service that can dynamically scale to handle various client load and arrival pattern. Formulated and tested different criterion for scaling to maximize client satisfaction with limited resources.
Timeline
Quantitative Trader
IMC Chicago
08.2023 - Current
Quantitative Trader Intern
IMC Financial Markets
06.2022 - 08.2022
Bachelor of Science - Computer Science, Computer Systems, Algorithms & Complexity, Mathematical Sciences
Carnegie Mellon University