As a Quantitative Engineer, you will work directly with the founders to build the trading and backtesting systems that power Conviction. You’ll develop quantitative strategies, work with large financial datasets, and turn trading ideas that can be tested and deployed in production.
What You’ll Do
- Execution & Trading Systems – Develop trade-generation and execution logic, with a focus on low-latency systems
- Backtesting – Build and improve backtesting systems that measure historical strategy performance
- Strategy Development – Build multi-agent systems that translate trading ideas into deployed, production-ready strategies
- Quantitative Research – Research, develop, and evaluate systematic trading strategies across equities, options, futures, and other financial markets
- Market Data – Work with large historical and real-time financial datasets, including prices, fundamentals, news, and alternative data
Qualifications & Experience
- Strong Python and quantitative programming skills
- Experience building or researching systematic trading strategies
- Strong understanding of statistics, probability, and quantitative methods
- Experience working with large financial or time-series datasets
- Experience designing and evaluating backtests
- Understanding of common sources of backtest error, including look-ahead bias, survivorship bias, overfitting, transaction costs, and data leakage
- Understanding of financial markets, order types, market structure, and trade execution
- Experience with data analysis libraries and quantitative research tooling
Preferred Qualifications
We’re especially interested in people who have worked in quantitative finance, trading, machine learning, or financial markets. Previous experience at a hedge fund, proprietary trading firm, asset manager, fintech company, market data provider, or quantitative research group is a plus.