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Trading Backtesting Jobs (NOW HIRING)

Point72

Macro Quantitative Researcher

New York, NY · On-site

Develop systematic trading models across global futures (equity indices, commodities and fixed income) and/or FX markets * Alpha idea generation, backtesting, and implementation * Evaluate new ...

Point72

Macro Quantitative Researcher

New York, NY

Develop systematic trading models across global futures (equity indices, commodities and fixed income) and/or FX markets * Alpha idea generation, backtesting, and implementation * Evaluate new ...

Geneva Trading

Junior Software Engineer

Chicago, IL · On-site

$80K - $130K/yr

Founded in 1999, Geneva Trading is a premier global principal trading firm with strategically ... Leverage Python to build high-speed data pipelines, backtesting frameworks, and real-time ...

Belvedere Trading

Quantitative Researcher

Chicago, IL · On-site

$140K - $200K/yr

Build, improve, and maintain research tools (e.g., Python, Jupyter) for testing, backtesting, validating, and monitoring models and strategies. * Collaborate closely with traders, technologists, and ...

Belvedere Trading

Quantitative Researcher

Chicago, IL · On-site

$140K - $200K/yr

Build, improve, and maintain research tools (e.g., Python, Jupyter) for testing, backtesting, validating, and monitoring models and strategies. * Collaborate closely with traders, technologists, and ...

TechChain Talent

Staff AI Engineer

Los Angeles, CA

$175K - $250K/yr

Build feedback loop from trade outcomes strategy improvement * Develop evaluation frameworks for signals and performance * Automate strategy generation and backtesting * Detect market regime shifts ...

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Trading Backtesting information

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How much do trading backtesting jobs pay per hour?

As of May 31, 2026, the average hourly pay for trading backtesting in the United States is $36.54, according to ZipRecruiter salary data. Most workers in this role earn between $22.36 and $46.15 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in Trading Backtesting, and why are they important?

To thrive in Trading Backtesting, you need strong quantitative analysis skills, knowledge of financial markets, and proficiency in programming—typically with a degree in finance, mathematics, or computer science. Familiarity with tools like Python, R, MATLAB, and backtesting platforms (e.g., QuantConnect, Backtrader) is essential, along with experience using historical data sets. Attention to detail, problem-solving abilities, and effective communication help you design robust strategies and collaborate with traders or quantitative teams. These skills are crucial to ensure the accuracy, reliability, and practical application of trading strategies before real-world implementation.

What are some common challenges faced by professionals conducting trading backtesting, and how can they be addressed?

One common challenge in trading backtesting is ensuring that historical data is both accurate and clean, as errors or missing data can skew results. Another challenge is avoiding overfitting trading strategies to past data, which can lead to poor real-world performance. Professionals often address these issues by sourcing reliable data providers, applying robust data cleaning processes, and using out-of-sample testing to validate strategies. Collaboration with quantitative analysts and software engineers is also key to building reliable backtesting frameworks.

What is trading backtesting?

Trading backtesting is the process of evaluating a trading strategy or model by applying it to historical market data to see how it would have performed in the past. This helps traders and analysts assess the viability and potential profitability of a strategy before risking real capital. By simulating trades over previous market conditions, backtesting can reveal strengths, weaknesses, and possible improvements in the trading approach. However, it's important to note that past performance does not guarantee future results, and overfitting to historical data can lead to misleading conclusions.

What is the difference between Trading Backtesting vs Trading Analyst?

AspectTrading BacktestingTrading Analyst
Primary FocusTesting trading strategies using historical dataAnalyzing market data and trading performance
Skills RequiredQuantitative analysis, programming, data analysisMarket analysis, reporting, communication
Work EnvironmentQuantitative teams, trading firms, hedge fundsFinancial institutions, asset management firms
CertificationsNone specific, often requires programming or finance backgroundChartered Financial Analyst (CFA), financial modeling certifications

Trading Backtesting involves testing trading strategies against historical data to evaluate their effectiveness, often requiring programming and quantitative skills. Trading Analysts focus on analyzing market trends, providing insights, and supporting trading decisions through data analysis and reporting. While both roles involve market data, backtesting is more technical and strategy-focused, whereas trading analysis emphasizes market understanding and communication.

Infographic showing various Trading Backtesting job openings in the United States as of May 2026, with employment types broken down into 100% Full Time. Highlights an 83% In-person, and 17% Remote job distribution, with an average salary of $76,005 per year, or $36.5 per hour.
Macro Quantitative Researcher

Macro Quantitative Researcher

Point72

New York, NY • On-site

Full-time

Posted 23 days ago

Job description

About the Team:
A well-established quantitative portfolio management team at Point72 is looking for an experienced quantitative professional in the intraday to mid frequency systematic macro space. The candidate will be given the resources and support to drive the build out and expansion of the quantitative macro business.
Role:
  • Perform rigorous and innovative research to develop systematic signals for global macro (futures, FX, etc.) markets
  • Work with price-volume and alternative data at intraday to multiday (up to 2-3 weeks) horizons in the mid-frequency space
  • Participate in the research pipeline end-to-end, including signal idea generation, data processing, modeling, strategy backtesting, and production implementation
  • Work in a team of highly qualified and motivated individuals with access to a cutting-edge research and trading infrastructure and clean datasets

Responsibilities:
  • Develop systematic trading models across global futures (equity indices, commodities and fixed income) and/or FX markets
  • Alpha idea generation, backtesting, and implementation
  • Evaluate new datasets for alpha potential
  • Contribute to and enhance portfolio optimization, allocation and risk management processes
  • Help drive the growth of the investment process and research capabilities of the team
  • Assist in building, maintenance, and continual improvement of production and trading environments

Requirements:
  • MS or PhD in physics, engineering, statistics, applied math, quantitative finance, or other quantitative fields with a strong foundation in statistics
  • 4+ years of signal research or portfolio management experience in futures markets and/or FX as part of a successful proprietary trading team with a track record
  • Prior professional experience with signal combination, portfolio optimization and risk management
  • Demonstrated proficiency in Python, R, or C/C++. Familiarly with data science toolkits, such as scikit-learn, Pandas
  • Collaborative mindset with strong independent research abilities
  • Commitment to the highest ethical standards

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