Develop, implement, and maintain quantitative measures of liquidity risk using advanced mathematical/statistical/engineering approaches * Perform quantitative analysis and facilitate understanding of ...
Develop, implement, and maintain quantitative measures of liquidity risk using advanced mathematical/statistical/engineering approaches * Perform quantitative analysis and facilitate understanding of ...
Develop, implement, and maintain quantitative measures of liquidity risk using advanced mathematical/statistical/engineering approaches * Perform quantitative analysis and facilitate understanding of ...
Develop, implement, and maintain quantitative measures of liquidity risk using advanced mathematical/statistical/engineering approaches * Perform quantitative analysis and facilitate understanding of ...
Corporate Treasury, Liquidity Meterics Strats, Quantitative Engineering, Dallas, Vice President
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Develop, implement, and maintain quantitative measures of liquidity risk using advanced mathematical/statistical/engineering approaches * Perform quantitative analysis and facilitate understanding of ...
Corporate Treasury, Liquidity Meterics Strats, Quantitative Engineering, Dallas, Vice President
Dallas, TX · On-site
Develop, implement, and maintain quantitative measures of liquidity risk using advanced mathematical/statistical/engineering approaches * Perform quantitative analysis and facilitate understanding of ...
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Statistical Engineering information
See Texas salary details
$55.3K - $56.9K
6% of jobs
$56.9K - $58.4K
8% of jobs
$60K is the 25th percentile. Wages below this are outliers.
$58.4K - $60K
10% of jobs
$60K - $61.5K
8% of jobs
$61.5K - $63.1K
10% of jobs
The median wage is $64.2K / yr.
$63.1K - $64.6K
8% of jobs
$64.6K - $66.2K
10% of jobs
$66.2K - $67.7K
8% of jobs
$68.4K is the 75th percentile. Wages above this are outliers.
$67.7K - $69.3K
10% of jobs
$69.3K - $70.9K
8% of jobs
$70.9K - $72.4K
10% of jobs
$55.3K
$64.9K
$72.4K
How much do statistical engineering jobs pay per year?
As of May 30, 2026, the average yearly pay for statistical engineering in Texas is $64,887.00, according to ZipRecruiter salary data. Most workers in this role earn between $60,300.00 and $69,300.00 per year, depending on experience, location, and employer.
What are the key skills and qualifications needed to thrive as a Statistical Engineer, and why are they important?
To thrive as a Statistical Engineer, you need strong quantitative analysis skills, a background in statistics or mathematics, and often a relevant degree such as in engineering or applied statistics. Proficiency with statistical software (e.g., R, SAS, Python), data management systems, and sometimes Six Sigma certification is typically required. Critical thinking, problem-solving, and clear communication are crucial soft skills for interpreting data and collaborating with multidisciplinary teams. These skills ensure accurate data-driven decisions, efficient process improvements, and effective solutions to complex engineering challenges.
How does a Statistical Engineer typically collaborate with cross-functional teams to implement data-driven solutions?
Statistical Engineers frequently work alongside data scientists, software engineers, and business analysts to design and implement robust data-driven solutions. They are responsible for translating complex statistical models into actionable insights and ensuring that these models are integrated effectively within existing systems. Collaboration often involves regular meetings to align on project goals, sharing progress updates, and troubleshooting technical challenges together. This interdisciplinary teamwork is essential for ensuring that statistical methodologies are not only theoretically sound but also practically applicable to real-world business problems.
What is statistical engineering?
Statistical engineering is an interdisciplinary field that focuses on the integration and application of statistical methods and principles to solve complex, large-scale problems in science, business, and engineering. It involves designing data collection processes, analyzing and interpreting data, and implementing statistical solutions within larger systems. Statistical engineers often work on projects that require collaboration with other engineering disciplines, using statistics as a foundational tool to drive decision-making and innovation.
What is the difference between Statistical Engineering vs Data Scientist?
| Aspect | Statistical Engineering | Data Scientist |
|---|---|---|
| Required credentials | Statistics, Data Analysis, Engineering | Statistics, Computer Science, Data Analysis |
| Work environment | Manufacturing, R&D, Engineering teams | Business, Tech, Research sectors |
| Employer usage | Optimizing processes, designing experiments | Building models, insights, predictive analytics |
Statistical Engineering focuses on applying statistical methods to improve engineering processes and product development, often within manufacturing or R&D settings. Data Scientists analyze large datasets to extract insights, build predictive models, and support business decisions. While both roles require strong statistical skills, Statistical Engineering emphasizes process optimization and experimental design, whereas Data Scientists focus on data-driven insights across diverse industries.
What are popular job titles related to Statistical Engineering jobs in Texas? For Statistical Engineering jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Statistical Engineering jobs in Texas look for? The top searched job categories for Statistical Engineering jobs in Texas are:
What cities in Texas are hiring for Statistical Engineering jobs? Cities in Texas with the most Statistical Engineering job openings:
Corporate Treasury, Liquidity Meterics Strats, Quantitative Engineering, Dallas, Vice President
Goldman Sachs, Inc.Dallas, TX
Other
Posted 11 days ago
Goldman Sachs rating
8.3
Based on 25 frontline employees who took The Breakroom Quiz
29th of 141 rated banks
Job description
LIQUIDITY METRICS STRATS
Liquidity and Prime Risk Strats use their engineering and mathematical background to identify and measure risk and to implement quantitative and technical risk modelling solutions. Successful Strats are highly analytical, driven to own commercial outcomes, and communicate with precision and clarity. As a part of the team, you will work with our key business partners and understand financial markets to quantify the firm's liquidity risk. You will also focus on developing quantitative models & scalable architecture.
RESPONSIBILITIES
- Develop, implement, and maintain quantitative measures of liquidity risk using advanced mathematical/statistical/engineering approaches
- Perform quantitative analysis and facilitate understanding of a variety of financial instruments, including secured funding transactions, collateral firm and client inventory, and loans and commitments
- Quantify and monitor measures of risk in different areas across the firm, such as prime brokerage, synthetic trading, and repo trading
- Work alongside revenue generating functions and corporate treasury to implement the liquidity regulatory requirements
- Communicate clearly complex mathematical concepts with internal and external stakeholders such as risk managers, senior management and regulators.
- Updating and maintaining risk models along with business growth and risk environment changes
- Developing and maintaining large scale risk infrastructures/systems in a compiled or scripting language
QUALIFICATIONS
- At least 7 years of prior experience in the financial industry, preferably in Capital Markets, Risk or Treasury functions
- Strong quantitative skills with an advanced degree in Mathematics, Physics, Engineering or other highly quantitative discipline
- Strong programming experience in at least one compiled or scripting language (e.g. C, C++, Java, Python)
- Strong written and verbal communication skills - ability to explain complex quantitative concepts to a non-technical audience
- Strong analytical and problem solving skills using math, statistics, and programming
- Demonstrated ability to learn technologies and apply
- Familiarity with financial markets, financial assets and liquidity risk management practices is a plus
ABOUT GOLDMAN SACHS
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. Learn more about our culture, benefits, and people at GS.com/careers.
What Goldman Sachs employees say
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Benefits
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Get the full story on Breakroom
About Goldman Sachs
Sourced by ZipRecruiter
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