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Backtesting Jobs (NOW HIRING)

Point72

Macro Quantitative Researcher

New York, NY · On-site

Alpha idea generation, backtesting, and implementation * Evaluate new datasets for alpha potential * Contribute to and enhance portfolio optimization, allocation and risk management processes * Help ...

Point72

Macro Quantitative Researcher

New York, NY · On-site

Alpha idea generation, backtesting, and implementation * Evaluate new datasets for alpha potential * Contribute to and enhance portfolio optimization, allocation and risk management processes * Help ...

SIG Susquehanna

$37 - $51/hr

Research, design, and develop systems used in backtesting and data analysis * Build Python-based applications and tools that deliver tactical analytics for trading decisions * Strategy monitoring and ...

IMC

Quantitative Developer - Python

Chicago, IL · On-site

$200K - $225K/yr

Design high-fidelity simulation and backtesting infrastructure that models latency, microstructure, and real-world constraints * Define, compute, and curate features across instruments, regimes, and ...

IMC

Quantitative Developer - Python

Chicago, IL · On-site

$200K - $225K/yr

Design high-fidelity simulation and backtesting infrastructure that models latency, microstructure, and real-world constraints * Define, compute, and curate features across instruments, regimes, and ...

Learn Beyond Consulting LLC

Java Developer

Jersey City, NJ · On-site

$53.25 - $69/hr

Experience with research and backtesting frameworks * Experience working with large-scale / high-frequency datasets * Strong software engineering practices: Git, testing, modular design * Linux and ...

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Backtesting information

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$42K

$102.4K

$150K

How much do backtesting jobs pay per year?

As of Sep 12, 2026, the average yearly pay for backtesting in the United States is $102,439.00, according to ZipRecruiter salary data. Most workers in this role earn between $83,500.00 and $119,000.00 per year, depending on experience, location, and employer.

What is backtesting?

Backtesting is the process of evaluating a trading strategy or investment model by applying it to historical market data. This helps traders and analysts see how the strategy would have performed in the past, which can provide insights into its potential effectiveness and risks. While backtesting can help identify strengths and weaknesses, it's important to remember that past performance is not always indicative of future results. The reliability of backtesting depends on data quality, strategy design, and how well it simulates real trading conditions.

What skills and qualifications are needed to thrive as a backtesting analyst?

To thrive as a Backtesting Analyst, you need a strong background in quantitative analysis, statistics, programming (typically in Python or R), and familiarity with financial markets, usually supported by a degree in mathematics, finance, or a related field. Proficiency with backtesting platforms (such as QuantConnect or Zipline), data analysis tools, and version control systems like Git is often required. Attention to detail, critical thinking, and strong problem-solving abilities are key soft skills that help ensure robust model evaluation and development. These skills are vital for accurately assessing trading strategies and minimizing risk in real-world financial applications.

What are common challenges faced when backtesting trading strategies, and how can they be managed?

One common challenge in backtesting trading strategies is the risk of overfitting, where a model performs exceptionally well on historical data but fails in live markets. Data quality and availability can also pose issues, as incomplete or inaccurate data may skew results. To manage these challenges, it's important to use out-of-sample testing, robust data cleaning processes, and to validate strategies on multiple datasets. Collaborating with quantitative analysts and developers can also help ensure the backtesting process is thorough and reliable.

What is the difference between Backtesting vs Quantitative Analyst?

AspectBacktestingQuantitative Analyst
Primary RoleTesting trading strategies using historical dataDeveloping and implementing quantitative models for investment decisions
Required SkillsData analysis, programming, finance knowledgeMathematics, programming, financial theory
Work EnvironmentTrading firms, hedge funds, financial institutionsAsset management firms, hedge funds, banks
CertificationsOften none required, but CFA or CQF helpfulCFA, CQF, or advanced degrees common

Backtesting focuses on evaluating trading strategies with historical data, while a Quantitative Analyst develops models to inform investment decisions. Both roles require strong analytical skills and finance knowledge but differ in scope and responsibilities.

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What states have the most Backtesting jobs?

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Backtesting jobs near you
Infographic showing various Backtesting job openings in the United States as of September 2026, with employment types broken down into 95% Full Time, 4% Part Time, and 1% Contract. Highlights an 82% Physical, 4% Hybrid, and 14% Remote job distribution, with an average salary of $102,439 per year, or $49.2 per hour.

Head of Systematic ETF Strategy Team (USA)

Stamford, CT • On-site

Trexquant Investment
Investment Management and Consulting Services • 1 - 10 employees
Learn more about Trexquant Investmentexternal

$130K - $200K/yr

Full-time

Medical, Dental, Vision

Re-posted 26 days ago

Job description

Trexquant is seeking an experienced quantitative researcher to lead our Systematic ETF Strategy Team. In this role, you will manage a team of researchers focused on designing, implementing, and trading systematic ETF-based strategies within Trexquant’s core quantitative framework. Your leadership will play a critical role in scaling ETF strategies into a meaningful asset class for the firm.

Responsibilities

  • Lead and mentor a team of researchers to expand ETF capabilities by identifying new data sources, signals, and strategies.
  • Oversee the design, backtesting, and implementation of systematic ETF trading strategies.
  • Collaborate with the development team to enhance the performance, robustness, and scalability of ETF simulation and trading infrastructure.
  • Partner with execution and financing teams to optimize trade execution and capital efficiency.
  • Work with the risk team to establish monitoring frameworks, controls, and capital allocation processes specific to ETF exposures.
  • Present ETF research initiatives and progress to senior management, ensuring alignment with firm-wide trading and investment strategies.

Requirements

  • 5+ years of experience researching and trading quantitative ETF-based strategies.
  • Bachelor’s, Master’s, or Ph.D. in Mathematics, Statistics, Computer Science, or a related STEM field.
  • Proven leadership experience managing quantitative research teams.
  • Strong quantitative, analytical, and problem-solving skills.
  • Proficiency in Python; familiarity with large-scale data analysis and backtesting frameworks a plus.

Benefits

  • Competitive salary with performance-based bonus.
  • Collaborative, casual, and friendly work environment.
  • PPO health, dental, and vision insurance fully covered for you and your dependents.
  • Pre-tax commuter benefits.
  • Weekly company-provided meals.

Applications are now open for our NYC office, opening in September 2026.

The base salary range is $130,000 to $200,000, depending on candidates’ educational and professional background. Base salary is only one part of Trexquant’s total compensation, which may include a discretionary and performance based bonus.

Trexquant is an Equal Opportunity Employer