ZipRecruiter

Log In

1

Trading Backtesting Jobs (NOW HIRING)

Swish Analytics

Trading Analyst

San Francisco, CA

Track record of building and backtesting quantitative models using real historical data; GitHub ... trading decisions * Familiarity with market microstructure concepts such as adverse selection ...

Swish Analytics

Trading Analyst

San Francisco, CA · On-site +1

Track record of building and backtesting quantitative models using real historical data; GitHub ... Department Trading Operations Locations San Francisco, CA - Remote Remote status Fully Remote

AEG

Trading Analyst

San Francisco, CA · On-site

$70K - $110K/yr

Track record of building and backtesting quantitative models using real historical data; GitHub ... trading decisions * Familiarity with market microstructure concepts such as adverse selection ...

next page

Showing results 1-20

People also search for

All JobsTrading Backtesting Jobs

Trading Backtesting information

See salary details

$14

$36

$50

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.
Lead Trading Systems Engineer (USA)

Lead Trading Systems Engineer (USA)

Trexquant Investment

Stamford, CT • On-site

$175K - $200K/yr

Full-time

Medical, Dental, Vision

Posted 6 days ago

Job description

Trexquant is looking for a senior technologist to lead the design and evolution of our core trading, research, and simulation infrastructure. This role involves architecting and building scalable, low-latency systems in Linux environments, collaborating closely with quantitative researchers & engineers, and driving next-generation simulation and execution platforms.
Responsibilities
  • Design, build, and enhance core infrastructure systems that support trading, research, and operations, including integration with the firm's Order Management System (OMS).
  • Architect and develop a high-performance multi-asset simulation and backtesting platform capable of supporting strategy research, backtesting, and deployment across equities, futures, fixed income, and derivatives.
  • Evaluate existing systems to identify bottlenecks and implement improvements that enhance scalability, performance, and security.
  • Collaborate with quantitative researchers and cross-functional teams to ensure the platform accurately models market dynamics, transaction costs, and execution behavior while aligning technical initiatives with a long-term infrastructure roadmap.
  • Design and optimize scalable data and compute infrastructure for low-latency, high-throughput processing of large-scale market data across simulation and production trading.
  • Improve caching, time-series management, and distributed computation while keeping the simulation & backtesting framework modular and scalable.
  • Oversee the development, integration, and deployment of systems and tools in C++, Python, and Linux environments.
  • Provide mentorship and technical guidance to engineers and researchers while staying current with emerging technologies and industry best practices.

Requirements
  • Bachelor's, Master's, or Ph.D. in Computer Science, Engineering, Mathematics, or a related STEM field.
  • 6+ years of experience building high-performance trading, simulation, or research infrastructure within Linux environments.
  • Expert-level proficiency in one of these programming languages: C++ (C++17/20), Java, or Python, with strong knowledge of algorithms, concurrency, data structures, and systems architecture. Preference for C++.
  • Experience architecting scalable, low-latency, high-throughput systems in Linux-based production environments.
  • Knowledge of market microstructure, execution systems, and simulation or backtesting methodologies.
  • Experience designing or supporting OMS, execution, or comparable trading infrastructure.
  • Excellent communication skills and ability to collaborate effectively across engineering and research teams.
  • Financial industry experience is a plus, but not required.

Benefits
  • Competitive salary plus bonus based on individual and company performance.
  • Collaborative, casual, and friendly work environment.
  • PPO Health, dental and vision insurance premiums fully covered for you and your. dependents.
  • Pre-tax commuter benefits.
  • Weekly company meals

Applications are open for both Stamford and New York City offices, the latter with a planned opening in October 2026.
The base salary range is $175,000 - $200,000 depending on the candidate's educational and professional background. Base salary is one component of Trexquant's total compensation, which may also include a discretionary, performance-based bonus. This position is classified as overtime-exempt.
Trexquant is an Equal Opportunity Employer

Apply