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Model Validation Jobs in Alabama (NOW HIRING)

New Car Model Engineer

Selma, AL · On-site

$55K - $65K/yr

New Model Engineer Surge Staffing Selma, Alabama, United States (On-site)SaveApply NEW MODEL ... This role supports engineering design, testing, validation, and implementation of new products ...

New Car Model Engineer

Selma, AL · On-site

$55K - $65K/yr

New Model Engineer Surge Staffing Selma, Alabama, United States (On-site)SaveApply NEW MODEL ... This role supports engineering design, testing, validation, and implementation of new products ...

Showing results 21-40

Model Validation information

See Alabama salary details

$20

$47

$70

How much do model validation jobs pay per hour?

As of Aug 7, 2026, the average hourly pay for model validation in Alabama is $47.13, according to ZipRecruiter salary data. Most workers in this role earn between $35.72 and $57.31 per hour, depending on experience, location, and employer.

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

To thrive as a Model Validation professional, you need strong quantitative, statistical, and analytical skills, often supported by a degree in mathematics, statistics, finance, or a related field. Proficiency with programming languages such as Python or R, statistical modeling software, and familiarity with regulatory guidelines like SR 11-7 or CCAR is essential. Outstanding attention to detail, problem-solving abilities, and clear communication are valuable soft skills in this role. These competencies are crucial for rigorously assessing complex models, documenting findings, and collaborating effectively with model developers and risk management teams.

What is a model validation?

A Model Validation job involves assessing and verifying the accuracy, reliability, and performance of mathematical and statistical models used in finance, risk management, or other industries. Professionals in this role conduct independent testing, evaluate assumptions, and ensure models comply with regulatory and internal standards. They identify weaknesses, suggest improvements, and help mitigate potential risks associated with model usage. Model validators often work with machine learning models, credit risk models, or trading algorithms, depending on the industry.

What are some common challenges faced by professionals in model validation roles?

One common challenge in Model Validation is staying up-to-date with evolving regulatory requirements and industry best practices, which can impact how models should be tested and documented. Model validators often work with highly complex financial or risk models, requiring strong analytical skills to assess underlying assumptions and potential risks. Additionally, balancing the need for thoroughness with tight deadlines and collaborating with model developers to address issues can be demanding. However, overcoming these challenges offers valuable opportunities to build expertise, work cross-functionally, and play a critical role in ensuring the integrity and reliability of key business decisions.

What are the most commonly searched types of Model Validation jobs in Alabama? The most popular types of Model Validation jobs in Alabama are:
What job categories do people searching Model Validation jobs in Alabama look for? The top searched job categories for Model Validation jobs in Alabama are:
What cities in Alabama are hiring for Model Validation jobs? Cities in Alabama with the most Model Validation job openings:
Infographic showing various Model Validation job openings in Alabama as of August 2026, with employment types broken down into 2% As Needed, 79% Full Time, 15% Part Time, 1% Temporary, and 3% Contract. Highlights an 89% Physical, 3% Hybrid, and 8% Remote job distribution, with an average salary of $98,028 per year, or $47.1 per hour.

DATA SCIENTIST (CYBER/CLOUD)

Quantum-Research-International,-Inc

Huntsville, AL • On-site

$110 - $140/hr

Other

Posted 14 days ago


Job description

DATA SCIENTIST (CYBER/CLOUD)

Full Time HUNTSVILLE, AL, HUNTSVILLE, AL, US


Quantum Research International, Inc. (Quantum) provides our national defense and federal civilian and industry customers with services and products in the following main areas: 1) Cybersecurity and Information Operations; 2) Space Operations and Control; 3) Aviation Systems; 4) Ground, Air and Missile Defense, and Fires Support Systems; 5) Intelligence Programs Support; 6) Experimentation and Test; 7) Program Management; and (8) Audio/Visual Technology Applications. Quantum's Corporate Office is located in Huntsville, AL, but Quantum actively hires for positions nationwide and internationally. We pride ourselves on providing high quality support to the U.S. Government and our Nation's Warfighters. In addition to our corporate office, we have physical locations in Aberdeen, MD; Colorado Springs, CO; Crestview, FL, Orlando, FL, and Tupelo, MS


Quantum Research Int is seeking a motivated Mid-Level (or Junior) Data Scientist to support advanced AI/ML and large language model (LLM) initiatives within a cybersecurity and risk analysis platform. You will contribute to the development, deployment, and integration of predictive models and LLM-based solutions to process structured and unstructured data (including SBOMs, CVEs, vulnerability data, and critical program information), generate actionable insights, and support data-informed decision making in a high-stakes defense environment.



  • Support the formulation, design, and execution of data-driven projects focused on cybersecurity risk prioritization, vulnerability analysis, exposure trends, anomaly detection, and automated risk reporting.

  • Develop, fine-tune, and assist in deploying AI/ML models and LLM-based solutions (e.g., for natural language understanding, summarization, and insight generation from unstructured sources such as SBOMs and technical documentation).

  • Help integrate model outputs into data pipelines, dashboards, and visualization tools to deliver clear insights for technical and non-technical stakeholders.

  • Collaborate with data analysts, software developers, and cross-functional teams to embed predictive analytics and LLM capabilities into existing platforms.

  • Clean, collate, and preprocess complex datasets from multiple sources; assess and improve data quality.

  • Apply statistical methods, machine learning algorithms, and LLM techniques to extract actionable insights under guidance.

  • Perform model validation, performance monitoring, and testing.

  • Optimize models for accuracy, scalability, and usability.

  • Produce and present reports, summaries, and visualizations that communicate findings and implications.

  • Stay current with advancements in AI/ML, LLMs, and cybersecurity data domains.

  • Contribute to MLOps practices including model versioning and deployment support.

  • Assist in LLM-driven techniques for assessing compromised datasets to gauge impact and score risk.



  • 2–5+ years of professional experience as a Data Scientist with emphasis on AI/ML model development and deployment (0–3 years for Junior level).

  • Bachelor's degree required; Master's preferred in Data Science, Computer Science, Statistics, Mathematics, or a closely related field.

  • Proficiency in Python (primary); experience with R is a plus.

  • Hands-on experience with ML frameworks (TensorFlow, PyTorch, Scikit-learn) and basic LLM implementation/fine-tuning (BERT, GPT-style models, LLaMA/Ollama, or equivalents).

  • Strong proficiency in data manipulation and analysis (Pandas, NumPy) and SQL.

  • Ability to translate technical outputs into clear, actionable insights and presentations.

  • Familiarity with cybersecurity data types and concepts (CVEs, SBOMs, vulnerability severity scoring, risk exposure metrics) or enterprise risk management domains is beneficial.

  • Active TS//SCI security clearance (or ability to obtain and maintain).

  • Preferred certs: CISSP, CySA+, Security+, CEH



  • Prior experience in cybersecurity, defense, national security, or enterprise risk management environments.

  • Experience integrating AI/ML or LLM solutions with cloud platforms (AWS SageMaker, Azure ML, GCP) or on-premises systems.

  • Knowledge of basic MLOps tools and practices.

  • Experience with business intelligence and dashboard tools (Tableau, Power BI).

  • Familiarity with big data frameworks or large-scale data processing.

  • Additional programming skills (Java, C++) are a plus.

  • Strong foundation in statistics, linear algebra, and experimental design.

  • This role combines technical AI/ML and LLM contributions with collaboration in a sensitive, cleared environment. Ideal candidates are proactive, eager to learn, and comfortable applying advanced modeling to real-world cybersecurity challenges.


Equal Opportunity Employer/Affirmative Action Employer M/F/D/V: All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, disability, veteran status, genetic information, sexual orientation, gender identity, or any other characteristic protected by law. *Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

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