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Predictive Modeling Jobs in California (NOW HIRING)

LMI

Data Scientist - Clearance Required

Fort Bragg, CA · On-site

Develop, test, and refine predictive models to forecast resource consumption and annual rate projections with a maximum error margin of 1%. * Apply statistical analysis, feature engineering, time ...

Hireblazer

Senior Data Scientist

Irvine, CA · On-site

Apply advanced statistical and predictive modeling techniques to optimize healthcare and digital experiences. Propose innovative solutions using data mining, statistical analysis, and machine ...

Gravity IT Resources

Data Scientist II

Mountain View, CA · On-site

$120 - $155/hr

Perform business analysis using statistical analysis, explanatory and predictive modeling, and data mining to develop actionable insights and recommendations for current business operations. * Work ...

New

Wing

Senior Data Scientist

Palo Alto, CA · On-site +1

They analyze complex datasets, design and train robust predictive models, and conduct rigorous statistical analysis to evaluate tradeoffs, quantify impact, and guide strategic choices. They ...

Esri

Product Analyst

Redlands, CA · On-site

... predictive modeling to product sales, usage, and customer data to inform strategy, pricing, and growth • Create executive ready reports, and deep analyses that clearly communicate analytical ...

Esri

Product Analyst

Redlands, CA · On-site

... predictive modeling to product sales, usage, and customer data to inform strategy, pricing, and growth • Create executive ready reports, and deep analyses that clearly communicate analytical ...

247Hire

Data Scientist

Los Angeles, CA · On-site

$120 - $160/hr

Build and iterate on predictive models to project content performance * Test different model types (e.g., gradient boosting, regression) and iterate based on accuracy and user interpretability needs

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Predictive Modeling information

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How much do predictive modeling jobs pay per hour?

As of Sep 5, 2026, the average hourly pay for predictive modeling in California is $57.94, according to ZipRecruiter salary data. Most workers in this role earn between $51.97 and $67.36 per hour, depending on experience, location, and employer.

What is predictive modeling?

A Predictive Modeling job involves using statistical techniques, machine learning algorithms, and data analysis to forecast future outcomes based on historical data. Professionals in this role build and test models to identify patterns, trends, and relationships in complex datasets. They commonly work in industries like finance, healthcare, and marketing to improve decision-making and optimize business processes. Strong skills in programming, data manipulation, and statistical analysis are essential for success in this role.

What does a typical workday look like for someone working in predictive modeling?

A typical day in predictive modeling involves gathering and cleaning data, selecting relevant features, and building statistical or machine learning models to forecast trends or behaviors. You’ll regularly use programming languages and analytics tools to test model performance and iterate on results, while documenting findings and preparing reports for internal teams or clients. Collaboration is often required with data engineers, subject matter experts, and business leaders to ensure that models align with organizational goals. Additionally, you may be tasked with presenting your insights to both technical and non-technical audiences, making strong communication skills essential for success in this role.

What are the key skills and qualifications needed to thrive in predictive modeling, and why are they important?

To thrive in Predictive Modeling, you need strong statistical analysis, data mining, and machine learning skills, often supported by a degree in statistics, computer science, mathematics, or a related field. Expertise with tools such as Python, R, SAS, or SQL, as well as knowledge of data visualization software, is commonly required, and certifications in data science or analytics are a plus. Strong problem-solving abilities, attention to detail, and effective communication are key soft skills for this role. Mastering these skills enables professionals to build accurate models, interpret data-driven results, and clearly communicate insights to stakeholders, which are critical for informed business decision-making.

What are the most commonly searched types of Predictive Modeling jobs in California?

The most popular types of Predictive Modeling jobs in California are:

What are popular job titles related to Predictive Modeling jobs in California?

For Predictive Modeling jobs in California, the most frequently searched job titles are:

What job categories do people searching Predictive Modeling jobs in California look for?

The top searched job categories for Predictive Modeling jobs in California are:

What cities in California are hiring for Predictive Modeling jobs?

Cities in California with the most Predictive Modeling job openings:

Predictive Modeling jobs near you
Infographic showing various Predictive Modeling job openings in California as of August 2026, with employment types broken down into 86% Full Time, 12% Part Time, and 2% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $120,524 per year, or $57.9 per hour.

Data Scientist - Clearance Required

LMI

Fort Bragg, CA • On-site

Full-time

Re-posted yesterday

Job description

Overview
LMI is seeking a Data Scientist to support a Special Operations Command (SOCOM) mission partner with advanced analytics, predictive modeling, natural language processing, and artificial intelligence and machine learning (AI/ML) product development.
The Data Scientist will analyze complex historical and operational datasets, convert data into machine-learning-ready formats, identify trends and predictive features, develop and validate statistical and machine learning models, and provide decision-quality insights that support resource forecasting, operational planning, and modernization. This position will work as part of a cross-functional data science product team to develop, integrate, govern, sustain, and document mission-relevant applications, dashboards, models, and research products.
LMI is a new breed of digital solutions provider dedicated to accelerating government impact with innovation and speed. Investing in technology and prototypes ahead of need, LMI brings commercial-grade platforms and mission-ready AI to federal agencies at commercial speed.
Leveraging our mission-ready technology and solutions, proven expertise in federal deployment, and strategic relationships, we enhance outcomes for the government efficiently and effectively. With a focus on agility and collaboration, LMI serves the defense, space, healthcare, and energy sectors-helping agencies navigate complexity and achieve mission success.
This position is on-site at Fort Bragg and requires an active Secret security clearance with the ability to obtain a Top Secret clearance.
Responsibilities
  • Analyze historical operational records, program execution data, and related datasets to identify trends, relationships, anomalies, and key features for predictive modeling.
  • Clean, normalize, reconcile, label, and transform structured and unstructured data from multiple sources into traceable, machine-learning-ready datasets.
  • Develop, test, and refine predictive models to forecast resource consumption and annual rate projections with a maximum error margin of 1%.
  • Apply statistical analysis, feature engineering, time-series forecasting, regression, ensemble methods, and other appropriate techniques to improve model accuracy, reliability, explainability, and operational usefulness.
  • Establish model validation, back-testing, sensitivity analysis, error analysis, and performance-monitoring methods; document assumptions, limitations, risks, and sources of uncertainty.
  • Develop natural language processing and generative AI solutions, including large language models tailored to approved business, operational, and intelligence use cases.
  • Develop projects that automate or augment human cognitive workload and respond rapidly to emerging operational data and data science requirements.
  • Collaborate with AI/ML engineers, data engineers, software developers, cybersecurity personnel, and mission stakeholders to integrate validated models and analytical outputs into secure web-based applications and enterprise workflows.
  • Support enterprise synchronization, integration, governance, security, sustainment, and adoption of data science and AI/ML products across multiple mission teams and stakeholder organizations.
  • Translate complex analytical findings into clear, actionable insights and recommendations for technical teams, program managers, operational users, and senior mission-partner leaders.
  • Develop and maintain customer-focused data science products, including applications, dashboards, analytical models, and research projects, through their full product life cycle.
  • Produce analytical reports, dashboards, briefings, and decision-support products that communicate trends, insights, model performance metrics, and recommendations.
  • Maintain comprehensive documentation of data sources, methodologies, feature definitions, model logic, validation results, system dependencies, workflows, and repeatable analytical processes.
  • Develop user guides, training materials, demonstrations, and knowledge-transfer products sufficient for a qualified practitioner to assume future operation and sustainment of the application or capability.
  • Provide rapid-response analytical and product-level staff augmentation based on changes in mission priorities and the operational environment.

Qualifications
Required Qualifications
  • Active Secret security clearance with the ability to obtain a Top Secret clearance.
  • Ability to work on-site at Fort Bragg, North Carolina.
  • Bachelor's degree in data science, statistics, mathematics, computer science, operations research, engineering, or a related quantitative field.
  • Five or more years of professional experience applying data science, advanced analytics, statistical modeling, or machine learning to complex real-world problems.
  • Demonstrated experience developing and validating predictive models, including time-series, regression, ensemble, or comparable forecasting methods.
  • Advanced proficiency with Python and SQL and practical experience with common data science and machine learning libraries; proficiency with R or a comparable analytical language may substitute where appropriate.
  • Strong knowledge of statistical analysis, feature engineering, model selection, hyperparameter tuning, cross-validation, error analysis, and performance measurement.
  • Experience preparing large, incomplete, inconsistent, structured, and unstructured datasets for repeatable analysis and model training.
  • Experience with natural language processing, generative AI, large language models, or retrieval-augmented generation in an applied environment.
  • Ability to evaluate model performance against stringent accuracy requirements and clearly communicate tradeoffs, risks, assumptions, and limitations.
  • Experience producing technical documentation, analytical reports, dashboards, briefings, and recommendations for technical and non-technical stakeholders.
  • Strong written and verbal communication skills and the ability to collaborate across data, engineering, software, security, governance, and operational teams.
  • Ability to independently manage multiple priorities and deliver high-quality analytical products in a fast-paced, mission-focused environment.
Preferred Qualifications
  • Master's degree or doctorate in data science, statistics, mathematics, computer science, operations research, engineering, or a related quantitative field.
  • Experience supporting SOCOM, U.S. Special Operations Forces, the Department of War, or another national security mission partner.
  • Experience developing models for resource consumption, demand, readiness, utilization, program execution, or annual planning forecasts.
  • Experience integrating analytical models into production web applications through APIs, services, containers, or reusable software components.
  • Familiarity with MLOps, DevSecOps, model monitoring, version control, automated testing, and continuous integration and continuous delivery practices.
  • Experience with secure cloud analytics environments such as AWS GovCloud or Azure Government and data visualization platforms such as Power BI or Tableau.
  • Familiarity with Agile delivery methods and experience working in cross-functional product or software development teams.
  • Experience supporting data governance, model governance, application sustainment, user adoption, and knowledge transfer for government data products.
Target Competencies
  • Mission Focus
  • Analytical Rigor
  • Technical Excellence
  • Product Ownership
  • Collaboration and Stakeholder Engagement
  • Clear Communication
  • Adaptability and Continuous Learning

Target Salary Range: $125,144 - $195,591
Disclaimer: The salary range displayed represents the typical salary range for this position and is not a guarantee of compensation. Individual salaries are determined by various factors including, but not limited to location, internal equity, business considerations, client contract requirements, and candidate qualifications, such as education, experience, skills, and security clearances.
#LI-SH1
Applicants must meet eligibility requirements for a U.S. Government security clearance. Only US Citizens are eligible for a security clearance. For this position, LMI will only consider applicants with security clearances or applicants who are eligible for security clearances, due to the nature of the work.
Job Locations
US-NC-Fort Bragg

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