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Java Quant Developer Jobs in Texas (NOW HIRING)

Experience solving analytical problems with quantitative approaches * Ability to excel in a fast ... Knowledge of developer tooling across the software development life cycle (task management, source ...

... Engineering, or a related quantitative field. b. c. d. * Experience: Minimum of 3-5 years of ... Languages: Professional proficiency in Python or Java. * Methodology: Deep familiarity with the ...

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How does a Java Quant Developer typically collaborate with quantitative analysts and traders within a financial firm?

As a Java Quant Developer, you will work closely with quantitative analysts (quants) and traders to translate complex mathematical models into robust, efficient code. Collaboration often involves frequent discussions to clarify model specifications, optimize algorithms for speed, and ensure accurate integration with trading platforms. You'll participate in code reviews, daily stand-ups, and sometimes even sit on the trading floor to gain firsthand insights into how your solutions impact trading strategies. This close teamwork helps ensure that models are delivered quickly and perform reliably in real-market conditions.

What are the key skills and qualifications needed to thrive as a Java Quant Developer, and why are they important?

To thrive as a Java Quant Developer, you need strong programming skills in Java, a solid grasp of quantitative finance, and typically a degree in computer science, mathematics, or a related field. Familiarity with financial libraries, statistical analysis tools, and experience using version control systems like Git are commonly expected, along with knowledge of databases such as SQL. Exceptional analytical thinking, problem-solving ability, and effective communication skills help you collaborate with traders and other stakeholders. These capabilities ensure the development of robust, efficient trading solutions that meet complex financial requirements and perform reliably in high-stakes environments.

What is a Java Quant Developer?

A Java Quant Developer is a software engineer who specializes in developing quantitative models and trading systems using the Java programming language. They work closely with quantitative analysts (quants) to implement mathematical models that help financial firms make trading decisions, manage risk, and analyze large datasets. Their responsibilities typically include designing, coding, testing, and optimizing high-performance applications for financial markets. A strong background in mathematics, finance, and computer science is usually required, along with expertise in Java and related technologies.
What are popular job titles related to Java Quant Developer jobs in Texas? For Java Quant Developer jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Java Quant Developer jobs in Texas look for? The top searched job categories for Java Quant Developer jobs in Texas are:
What cities in Texas are hiring for Java Quant Developer jobs? Cities in Texas with the most Java Quant Developer job openings:
Infographic showing various Java Quant Developer job openings in Texas as of May 2026, with employment types broken down into 96% Full Time, 3% Part Time, and 1% Contract. Highlights an 80% Physical, 5% Hybrid, and 15% Remote job distribution.
Engineering - Dallas - Vice President, Quantitative Engineering - 049460

Engineering - Dallas - Vice President, Quantitative Engineering - 049460

Goldman Sachs, Inc.

Dallas, TX

$178K - $229K/yr

Other

Posted 5 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: Vice President, Quantitative Engineering with Goldman Sachs & Co. LLC in Dallas, Texas. Multiple positions available. Lead the development, implementation, and documentation of 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. Mentor junior and mid-level team members.

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 three (3) years 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 five (5) years of experience in job offered or a related quantitative engineering role OR PhD 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. Prior experience must include three (3) years of experience (with a Master's degree) OR five (5) years of experience (with a Bachelor's degree) OR one (1) year of experience (with a PhD degree) with 5 of the 8 following skills: C++, Java, or Python; performing financial mathematics, including at least one of the following: stochastic calculus, no-arbitrage pricing theory, multivariable calculus, linear algebra, probability theory, numerical methods, or Monte-Carlo techniques; performing analysis leveraging market risk, credit risk, liquidity risk, or mathematical finance concepts; object-oriented programming and scripting programming languages such as Python or Java; implementing mathematical models or analytics in production-quality software; working with database query languages, such as SQL, MongoDB, or other data management tools to process large datasets; applying algorithms or data structures to write complex programs; and developing pricing models for financial products to model risk, economics, and cash flows under normal and distressed market environments.

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