Quantitative Developer Resume Sample

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William Tilson

Quantitative Developer

Where trading strategy meets production-grade code

+44 20 5550 0587
github.com/wtilson

Quantitative developer with eight years building the systems behind trading and quantitative research at hedge funds and a bank in London. Bridges quants and engineering — turning models and strategies into fast, robust production code, building backtesting and execution infrastructure, and handling the data pipelines that feed it all. Built a backtesting engine that cut strategy research turnaround from days to minutes for the quant team. Works in C++ and Python on low-latency systems, market and time-series data, risk and pricing libraries, and the performance optimisation trading demands. Strong on both the mathematics and the software engineering, and meticulous about correctness where bugs cost real money. Calm under live-trading pressure. Looking for a quant-developer role with a fund, bank or trading firm doing serious systematic work.

LocationLondon, UK
NationalityBritish
GenderMale
Notice Period3 months
Date of Birth1992-02-26
Work Experience
(April 2017 to Present)9 years & 3 months

London Systematic Capital - London, UK

Quantitative Developer

Turn the quant models and the strategies into fast, robust production trading code every day.
Built a backtesting engine that cut the strategy research turnaround from days down to minutes.
Build and maintain all the execution infrastructure and the low-latency systems in C++ and Python.
Develop the data pipelines feeding the market, the reference and the time-series data to research.
Maintain the pricing and risk libraries with rigorous testing where a bug costs real money.
Optimise the performance and support all of the trading systems calmly under real live-trading conditions.
(August 2014 to March 2017)2 years & 8 months

City Investment Bank - London, UK

Quant Developer / Software Engineer

Built pricing and risk tools for trading desks in C++ and Python.
Developed the data feeds and the analytics supporting the quant research teams.
Learned the market microstructure, backtesting and low-latency engineering on the job.
Gained CQF and moved to a systematic fund as a quant developer.
(June 2012 to July 2014)2 years & 2 months

City Investment Bank - London, UK

Software Engineer

Built backend systems and data tools as a software engineer in finance.
Learned the C++, Python and high-performance engineering on real production systems.
Built up the engineering depth that quant development is built on.
Then earned the move into a full quant-developer role from there.
Education
(September 2010 to June 2014)3 years & 10 months

University of Cambridge

MEng in Computer Science & Mathematics - Computer Science & Mathematics

Integrated master's combining computer science and mathematics, covering algorithms, numerical methods and software engineering. The blend maps exactly onto quant development. Built the dual foundation the role requires.
(January 2016 to December 2016)1 year

CQF Institute

Certificate in Quantitative Finance (CQF) - Quantitative Finance

Certificate in Quantitative Finance covering derivatives, risk, and computational finance methods. It deepened the finance domain alongside engineering. Applied directly to pricing, risk and backtesting systems.
Highlights

Days to minutes

Built a backtesting engine that cut strategy research turnaround from days to minutes for the quant team. Faster iteration lets researchers test far more ideas and find the ones that work.

Correct where it counts

Holds rigorous testing standards on code where a single bug can cost real trading money. In systematic trading, correctness is not optional, it is the whole job.
Key Projects

Low-Latency Execution System

Quant Developer (January 2019 to December 2019)

Built core components of a low-latency execution system in C++, tuning the hot path so orders went out within tight time budgets under live market load.

Market-Data Pipeline

Quant Developer (March 2020 to October 2020)

Designed the market and reference-data pipeline feeding research and live trading, making the feeds fast, clean and reproducible so models trained and ran on data they could trust.
Professional Skills
  • C++
  • Python
  • Backtesting Systems
  • Low-Latency Systems
  • Market & Time-Series Data
  • Pricing & Risk Libraries
  • Execution Infrastructure
  • Performance Optimisation
  • Numerical Methods
  • Data Pipelines
Certifications

Certificate in Quantitative Finance

CQF Institute (December 2016 to Present)

Certificate in Quantitative Finance covering derivatives, risk, and computational finance methods. It deepened the finance domain alongside engineering. Applied directly to pricing, risk and backtesting systems.

Low-Latency C++ & Systems

CppCon Training (April 2019 to Present)

Certification in low-latency C++ and high-performance systems engineering. It supports the execution infrastructure and the fast, correct trading code built for the desk.
Personal Skills
  • Analytical Thinking
  • Precision
  • Composure
  • Problem Solving
  • Rigour
Languages

English (UK)

Native or Bilingual Proficiency

Mandarin

Limited Working Proficiency
Activities & Interests

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