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Quantitative Engineer

ConvictionSoftware
Pay
$90K–$210K
per year
Work mode
On-site
Full Time
Level
Entry

San Francisco, CA at a glance

Rent
#2 of 51
$2,680/mo+46% vs US avg
Weather
#17 of 51
295 mild days0 hot · 0 cold
Income tax
#1 of 51
13.3% top rateCalifornia

What you need

  • Strong Python and quantitative programming skills
  • Experience building systematic trading strategies
  • Strong statistics and probability knowledge
  • Experience with large financial datasets
  • Understanding of backtest error sources

What you'll do

  • Develop low-latency trade-generation and execution logic
  • Build and improve backtesting systems
  • Build multi-agent trading strategy systems
  • Research systematic trading strategies across markets
  • Work with large financial and real-time datasets

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.

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About Conviction

Conviction lets you create and discover trading ideas, then monitors the market and acts on them for you. Start with any idea you have - or discover one from traders you follow on X or Reddit - and turn it into a strategy in natural language. Backtest it, paper trade it, deploy it and share what you learn.

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