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Quant Developer Jobs in Dallas, TX (NOW HIRING)

Advanced degree in quantitative analytics, economics, statistics, engineering, or a related area. * Minimum 4-5 years of experience in statistical/econometric modeling and database management.

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Quant Developer information

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$96.9K

$167.9K

$256.7K

How much do quant developer jobs pay per year?

As of Jun 9, 2026, the average yearly pay for quant developer in Dallas, TX is $167,873.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,000.00 and $196,800.00 per year, depending on experience, location, and employer.

What is a Quant Developer job?

A Quant Developer (Quantitative Developer) is a software engineer who builds and maintains financial models, trading systems, and analytical tools for quantitative analysts and traders. They use programming languages like Python, C++, or Java to develop algorithms that automate trading strategies, risk analysis, and data processing. Quant Developers typically work in hedge funds, investment banks, or proprietary trading firms, collaborating with quants and portfolio managers to optimize trading performance. Strong mathematical skills, proficiency in financial markets, and expertise in software development are essential for this role.

What are some typical challenges quant developers face in their daily work?

Quant developers often work with large, complex datasets and real-time data streams, which can present technical challenges related to performance, accuracy, and scalability. They may need to continuously adapt to changing market requirements or new financial regulations, requiring staying up to date and learning new tools or methods. Collaboration with quants, traders, and other stakeholders is common, so balancing technical problem-solving with effective communication is also important. These challenges make the role both demanding and intellectually rewarding for those passionate about technology and finance.

What are the key skills and qualifications needed to thrive in the Quant Developer position, and why are they important?

To thrive as a Quant Developer, you need advanced programming skills (often in Python, C++, or Java), a strong foundation in mathematics or statistics, and a relevant degree such as in computer science, engineering, or quantitative finance. Expertise in numerical libraries, version control systems like Git, and familiarity with financial modeling tools or industry data feeds is highly valuable. Collaboration, strong analytical thinking, and the ability to communicate complex concepts clearly are critical soft skills for this role. These capabilities are essential for designing robust quantitative models and working effectively with cross-functional teams in fast-paced financial environments.

What are the most commonly searched types of Quant Developer jobs in Dallas, TX? The most popular types of Quant Developer jobs in Dallas, TX are:
What job categories do people searching Quant Developer jobs in Dallas, TX look for? The top searched job categories for Quant Developer jobs in Dallas, TX are:
What cities near Dallas, TX are hiring for Quant Developer jobs? Cities near Dallas, TX with the most Quant Developer job openings:
Infographic showing various Quant Developer job openings in Dallas, TX as of June 2026, with employment types broken down into 50% Full Time, 25% Part Time, and 25% Contract. Highlights an 75% In-person, and 25% Remote job distribution, with an average salary of $167,873 per year, or $80.7 per hour.
Engineering - Dallas - Associate, Quantitative Engineering - 033664

Engineering - Dallas - Associate, Quantitative Engineering - 033664

Goldman Sachs

Dallas, TX • On-site

Other

Posted 11 days ago


Goldman Sachs rating

8.3

Company rating: 8.3 out of 10

Based on 25 frontline employees who took The Breakroom Quiz

29th of 141 rated banks


Job description

Job Duties: Associate, Quantitative Engineering with Goldman Sachs & Co. LLC in Dallas, Texas. Multiple positions available. Develop, implement, and document scenarios comprised of a broad range of economic and financial variables for businesses within the Firm. Collaborate with internal stakeholders, analyzing user needs from a scenario design perspective and addressing data, model, and implementation issues. Analyze large data sets (structured and unstructured) to build predictive models of business-relevant market variables. Develop, refine, and improve scenarios by leveraging knowledge in financial markets, economics, current events, statistical analysis, and programming. Build and challenge risk models, identify and quantify vulnerabilities across market, credit, liquidity risk and modeling. Create and maintain clear and complete technical documentation of the risk-model performance testing approach and process.

Job Requirements: Master's degree (U.S. or foreign equivalent) in Computer Science, Financial Engineering, Applied Mathematics, Data Science, Operations Research or related quantitative field and one (1) year of experience in job offered or a related quantitative engineering role OR Bachelor's degree (U.S. or foreign equivalent) in Computer Science, Financial Engineering, Applied Mathematics, Data Science, Operations Research or related quantitative field and two (2) years of experience in job offered or a related quantitative engineering role. Prior experience must include one (1) year of experience (with a Master's degree) OR two (2) years of experience (with a Bachelor's degree) with 5 of the 7 following skills: C++, Java, or Python; developing probability and pricing models utilizing financial mathematics principles, including stochastic calculus, no-arbitrage pricing theory, partial differential equations, multivariable calculus, linear algebra, numerical methods, optimization, probability, or random processes; quantitative analysis and model development using advanced econometric, statistical, and mathematical techniques, including Bayesian analysis, time series analysis, or machine learning algorithms; performing risk management or scenario-based analysis; developing quantitative risk analytics, including factor models; developing rigorous and scalable data management and analysis tools to provide risk oversight and support the investment process; and statistics and data driven performance analysis, including Linear Regression or Time Series Analysis to measure performance.

The Goldman Sachs Group, Inc., 2026. All rights reserved. Goldman Sachs is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, national origin, age, veteran status, disability, or any other characteristic protected by applicable law.


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About Goldman Sachs

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At Goldman Sachs, we commit our people, capital and ideas to help our clients, shareholders and the communities we serve to grow. Founded in 1869, we are a leading global investment banking, securities and investment management firm. Headquartered in New York, we maintain offices around the world. We believe who you are makes you better at what you do. We're committed to fostering and advancing diversity and inclusion in our own workplace and beyond by ensuring every individual within our firm has a number of opportunities to grow professionally and personally, from our training and development opportunities and firmwide networks to benefits, wellness and personal finance offerings and mindfulness programs.

Industry

Finance and insurance

Company size

10,000+ Employees

Headquarters location

New York, NY, US

Year founded

1869