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Uncertainty Quantification Jobs in Texas (NOW HIRING)

Leidos

Spaceflight Data Scientist (NASA HHPC)

Houston, TX · On-site

$107K - $195K/yr

Conduct formal uncertainty quantification, sensitivity analysis, and scenario exploration grounded in advanced decision theory. * Clearly communicate assumptions, decision logic, analytic results ...

Apple

Data Scientist, AI/ML Model Quality

Austin, TX

$142K - $263K/yr

Familiarity with confidence calibration techniques and uncertainty quantification. Experience with ML monitoring or observability platforms (e.g., MLflow, Weights & Biases, or equivalent). Experience ...

Visa

Sr. SW AI Engineer

Austin, TX · On-site

$121K - $160K/yr

Build confidence scoring and uncertainty quantification mechanisms for AI-generated outputs, including threshold-based routing of low-confidence results to human review. * Implement agent feedback ...

Apple

Data Scientist, AI/ML Model Quality

Austin, TX

$142K - $263K/yr

Familiarity with confidence calibration techniques and uncertainty quantification. Experience with ML monitoring or observability platforms (e.g., MLflow, Weights & Biases, or equivalent). Experience ...

ExxonMobil

Development Planning Advisor

Spring, TX · On-site

Capability in risk and uncertainty identification and quantification including likelihood * Excellent communication skills and ability to demonstrate to management strategic tradeoffs that show value ...

ExxonMobil

Development Planning Advisor

Spring, TX

Capability in risk and uncertainty identification and quantification including likelihood * Excellent communication skills and ability to demonstrate to management strategic tradeoffs that show value ...

ExxonMobil

Development Planning Advisor

Spring, TX · On-site

Capability in risk and uncertainty identification and quantification including likelihood * Excellent communication skills and ability to demonstrate to management strategic tradeoffs that show value ...

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Uncertainty Quantification information

What is uncertainty quantification?

Uncertainty Quantification (UQ) is the science of quantifying, managing, and reducing uncertainties in computational models and real-world systems. It involves identifying sources of uncertainty in data, model parameters, and algorithms, then using statistical and mathematical methods to assess their impact on model predictions. UQ is essential in fields like engineering, finance, and environmental science to ensure that predictions and decisions are robust and reliable. Practitioners use techniques such as sensitivity analysis, probabilistic modeling, and Monte Carlo simulations to quantify and analyze uncertainties.

What are the key skills and qualifications needed to thrive as an uncertainty quantification specialist?

To thrive as an Uncertainty Quantification Specialist, you need a strong background in applied mathematics, statistics, and computational modeling, often supported by an advanced degree in a quantitative field. Familiarity with programming languages such as Python or MATLAB, and experience with simulation tools and statistical analysis software, are typically required. Strong problem-solving skills, attention to detail, and effective communication help professionals convey complex concepts to interdisciplinary teams. These skills are crucial for accurately assessing risks, making data-driven decisions, and improving the reliability of models in engineering, finance, or scientific research.

What are some common challenges faced by professionals in uncertainty quantification when working on multidisciplinary teams?

Professionals in Uncertainty Quantification (UQ) often collaborate with experts from fields like engineering, data science, and physics. A common challenge is communicating complex statistical concepts in an accessible way to team members without a quantitative background. Additionally, integrating uncertainty models into existing workflows and ensuring that all stakeholders understand how uncertainty impacts decision-making can be demanding. Effective UQ professionals are proactive in facilitating clear communication and tailoring their approach to fit the needs of diverse teams.

What is the difference between Uncertainty Quantification vs Data Scientist?

AspectUncertainty QuantificationData Scientist
Required credentialsAdvanced degrees in engineering, mathematics, or statisticsDegree in computer science, statistics, or related fields
Work environmentResearch labs, engineering firms, simulation-based industriesTech companies, finance, healthcare, and marketing
Industry usageEngineering, aerospace, manufacturing, scientific researchBusiness analytics, product development, predictive modeling

Uncertainty Quantification focuses on assessing and reducing uncertainty in models and simulations, often requiring advanced mathematical skills. Data Scientists analyze data to extract insights, build predictive models, and support decision-making. While both roles involve statistics and data analysis, Uncertainty Quantification is more specialized in modeling uncertainties in engineering and scientific contexts, whereas Data Scientists work across diverse industries with a broader focus on data-driven insights.

What are popular job titles related to Uncertainty Quantification jobs in Texas?

For Uncertainty Quantification jobs in Texas, the most frequently searched job titles are:

What job categories do people searching Uncertainty Quantification jobs in Texas look for?

The top searched job categories for Uncertainty Quantification jobs in Texas are:

Uncertainty Quantification jobs near you
Infographic showing various Uncertainty Quantification job openings in Texas as of August 2026, with employment types broken down into 76% Full Time, 22% Part Time, and 2% Contract. Highlights an 78% Physical, 3% Hybrid, and 19% Remote job distribution.

Spaceflight Data Scientist (NASA HHPC)

Leidos

Houston, TX • On-site

$107K - $195K/yr

Full-time

Re-posted 4 hours ago

Leidos rating

8.3

Company rating: 8.3 out of 10

Based on 152 frontline employees who took The Breakroom Quiz

79th of 495 rated business services

Job description

On the Human Health and Performance Contract we are at the forefront of safeguarding astronaut health, ensuring human performance, and advancing technologies for human space exploration. We are seeking a Spaceflight Data Scientist with deep expertise in Bayesian inference, Bayesian decision theory, and normative decision theory to contribute to NASA's Mars Backwards Planetary Protection efforts to support the Statistics and Data Science team for the Biomedical Research and Environmental Sciences division at the NASA Johnson Space Center (JSC) in Houston, TX.
What You'll Do:
In this highly specialized role, you will build rigorous, mathematically grounded frameworks that inform critical decisions regarding contamination risk, biosafety protocols, evidence-evaluation strategies, and risk-management tradeoffs for Mars sample return and human/robotic exploration. Your work will directly influence policies and operational strategies that protect Earth's biosphere while enabling scientific advancement. You will help define the decision frameworks that safeguard Earth during one of the most significant scientific endeavors of our time. Your contributions will shape how humanity explores Mars, evaluates extraterrestrial samples, and manages biosafety risks across multiple mission architectures. This is a rare opportunity to apply high-level decision science to challenges at the frontier of planetary exploration, astrobiology, and human spaceflight.
This position is 100% on site and in person. Occasional travel may be required.
Primary Responsibilities:
  • Develop, implement, and compare Bayesian decision-theoretic and normative decision-analytic models to guide contamination-risk and policy decisions for Mars sample return and backwards planetary protection.
  • Construct probabilistic models that integrate microbial, environmental, and operational uncertainties across Mars-to-Earth transfer pathways.
  • Determine optimal testing, containment and mitigation strategies by quantifying tradeoffs among evidence, stakeholder values, mission constraints, and risk tolerances.
  • Conduct formal uncertainty quantification, sensitivity analysis, and scenario exploration grounded in advanced decision theory.
  • Clearly communicate assumptions, decision logic, analytic results, and policy implications to interdisciplinary teams, mission planners, and regulatory partners.
  • Contribute to compliance documentation and ensure analytical rigor in support of NASA's protective mandates.

Required Education and Experience:
  • Master's Degree and 10 years of experience or Ph.D. and 5 years of experience in Decision Sciences, Statistics, Health Economics, Operations Research, or a related quantitative discipline.
  • Demonstrated expertise in Bayesian inference, Bayesian decision theory, and normative decision theory, including eliciting priors, utilities, and multi-attribute value structures.
  • Proficiency with probabilistic programming tools such as Stan, R, Python, or equivalent.
  • Strong foundation in experimental design, probabilistic modeling, and formal risk-assessment methodologies.
  • Exceptional analytical rigor and quantitative problem-solving abilities.
  • Ability to communicate complex technical concepts to diverse audiences.
  • Collaborative mindset suited for interdisciplinary research and operational teams.
  • Strong attention to detail, particularly in documentation and model governance.

Desired Skills:
  • Experience applying decision theory to planetary protection, astrobiology, microbial risk assessment, or high-stakes biosafety domains.
  • Familiarity with COSPAR Planetary Protection guidelines and NASA risk-based decision processes.
  • Background in modeling for Mars Sample Return or similar exploration missions with stringent biosafety considerations.
  • Prior support of NASA programs or spaceflight research.

Must be able to obtain a Public Trust Clearance; due to contract requirements, U.S. Citizenship or U.S. Permanent residency is required.
If you're looking for comfort, keep scrolling. At Leidos, we outthink, outbuild, and outpace the status quo - because the mission demands it. We're not hiring followers. We're recruiting the ones who disrupt, provoke, and refuse to fail. Step 10 is ancient history. We're already at step 30 - and moving faster than anyone else dares.
Original Posting:
July 24, 2026
For U.S. Positions: While subject to change based on business needs, Leidos reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above.
Pay Range:
Pay Range $107,900.00 - $195,050.00
The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.

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About Leidos

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At Leidos, we deliver innovative solutions through the efforts of our diverse and talented people who are dedicated to our customers' success. We empower our teams, contribute to our communities, and operate sustainable practices. Everything we do is built on a commitment to do the right thing for our customers, our people, and our community.

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Company size

10,000+ Employees

Headquarters location

Reston, VA, US

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