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Backtesting Jobs in Washington, DC (NOW HIRING)

Phase2 Technology

Cybersecurity Data Scientist

Mclean, VA · On-site

$77.60 - $176/hr

Apply rigorous experimentation, statistical analysis, and evaluation methods, including precision/recall, drift, calibration, A/B testing, and backtesting against historical incidents to validate ...

All JobsBacktesting JobsBacktesting Jobs in Washington, DC

Backtesting information

See Washington, DC salary details

$47.6K

$116K

$169.9K

How much do backtesting jobs pay per year?

As of Aug 20, 2026, the average yearly pay for backtesting in Washington, DC is $116,022.00, according to ZipRecruiter salary data. Most workers in this role earn between $94,600.00 and $134,800.00 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.

What are popular job titles related to Backtesting jobs in Washington, DC?

For Backtesting jobs in Washington, DC, the most frequently searched job titles are:

What job categories do people searching Backtesting jobs in Washington, DC look for?

The top searched job categories for Backtesting jobs in Washington, DC are:

Backtesting jobs near you
Infographic showing various Backtesting job openings in Washington, DC as of August 2026, with employment types broken down into 95% Full Time, and 5% Contract. Highlights an 76% In-person, 10% Hybrid, and 14% Remote job distribution, with an average salary of $116,022 per year, or $55.8 per hour.

Data Scientist with Security Clearance

Kruger Recruiting

Washington, DC • On-site

Other

This job post has expired today. Applications are no longer accepted.

Job description

We are seeking a Senior Data Scientist with a strong sense of ownership to join our Platform team. This position has career growth opportunities for those seeking to become Lead Data Scientist and/or Team Manager. As a Data Scientist, you will
Use the capabilities of our AI Platform to deploy production solutions for our customers.
Work with customer data and own the development of an AI solution from ideation to production
Leverage integrations with big data frameworks (e.g. Databricks) as needed to develop solutions for customers. Primary Focus: Exploratory data analysis, model selection, feature engineering, hyperparameter tuning, setting up backtesting/evaluation frameworks, and some data engineering and SWE tasks Technical Skills: Foundational knowledge in data science/ML/CS Core Strengths: Choosing appropriate models, analyzing data, communicating business insights Tech Stack: Python data science stack (e.g., pandas, scikit-learn, pytorch, plotly, etc.) Engineering Tasks: Implement model training pipelines, create plots and visualizations to communicate insights, write re-usable modeling code Collaborative Aspect: Works closely with MLEs, other data scientists, product, customer success, QA MUST HAVE: A BA or greater in Data Science or Math or equivalent.

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