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Predictive Modeler Jobs in Texas (NOW HIRING)

Cliff Services Inc

Data Scientist

Dallas, TX · On-site

Dallas, TX Hybrid Role Summary Data Scientists bridge raw data and actionable business insights - building predictive models, running experiments, and communicating findings to both technical and non ...

Cliff Services Inc

Data Scientist

Frisco, TX · On-site

Genuine H1B, USC Role Summary Data Scientists bridge raw data and actionable business insights - building predictive models, running experiments, and communicating findings to both technical and non ...

Munich Re

Data Scientist, AI

Houston, TX · On-site +1

We focus on developing and maintaining predictive models that support all domains across the business. In this role, you'll collaborate closely with senior data scientists to build and support AI/ML ...

Munich Re

Data Scientist, AI

Arlington, TX · On-site +1

We focus on developing and maintaining predictive models that support all domains across the business. In this role, you'll collaborate closely with senior data scientists to build and support AI/ML ...

Inizio Partners

Data Scientist

Dallas, TX

$90K - $110K/hr

The role requires a strong understanding of statistical inference, causal analysis, and predictive modeling to help translate business questions into rigorous analytical solutions. The candidate ...

CoStar

Land.com - Senior Data Scientist

Austin, TX

This role will focus primarily on expanding AV+ parcel-level land valuation and predictive modeling capabilities in collaboration with internal engineering and product teams. The ideal candidate ...

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Predictive Modeler information

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$9

$54

$77

How much do predictive modeler jobs pay per hour?

As of Jun 25, 2026, the average hourly pay for predictive modeler in Texas is $54.70, according to ZipRecruiter salary data. Most workers in this role earn between $49.04 and $63.61 per hour, depending on experience, location, and employer.

How does a Predictive Modeler typically collaborate with data scientists and business stakeholders during a project?

Predictive Modelers work closely with data scientists to ensure that models are statistically sound and meet technical requirements, often sharing insights on data preprocessing and feature engineering. They also collaborate with business stakeholders to understand project goals, translate business problems into analytical tasks, and explain model outcomes in accessible terms. Regular communication and feedback loops help ensure that the developed models align with business objectives and deliver actionable insights. This collaborative approach is essential for successful project delivery and for ensuring that predictive solutions provide real value.

What are predictive modelers?

Predictive modelers are professionals who use statistical techniques, machine learning, and data analysis to develop models that forecast future outcomes based on historical data. They work in various industries, such as finance, healthcare, and marketing, to help organizations make data-driven decisions and anticipate trends or risks. Predictive modelers typically use tools like Python, R, or specialized software, and their work can involve data cleaning, selecting appropriate algorithms, and validating model performance. Their insights help businesses optimize processes, reduce costs, and improve customer satisfaction.

What is the difference between Predictive Modeler vs Data Analyst?

AspectPredictive ModelerData Analyst
Required CredentialsBachelor's or Master's in Statistics, Data Science, or related fields; often certifications in modeling or analyticsBachelor's in Statistics, Data Analysis, or related fields; certifications in data visualization or analysis tools
Work EnvironmentData science teams, analytics departments, often in tech, finance, or healthcare industriesBusiness units, marketing, finance, or operations teams across various industries
Employer & Industry UsageUsed for building predictive models to forecast trends and behaviorsUsed for interpreting data, generating reports, and providing insights

While both roles analyze data, Predictive Modelers focus on creating models to forecast future outcomes, whereas Data Analysts interpret existing data to inform decisions. Predictive Modelers typically require advanced statistical skills and modeling expertise, making their role more specialized in predictive analytics.

What are the key skills and qualifications needed to thrive as a Predictive Modeler, and why are they important?

To thrive as a Predictive Modeler, you need a strong background in statistics, mathematics, and data analysis, often supported by a degree in a quantitative field such as statistics, mathematics, or computer science. Familiarity with programming languages like Python or R, experience with machine learning frameworks, and knowledge of data visualization tools are typically required. Analytical thinking, problem-solving, and effective communication are standout soft skills for translating complex data into actionable insights. These skills and qualities are crucial for building accurate models that drive informed business decisions and add strategic value.
What cities in Texas are hiring for Predictive Modeler jobs? Cities in Texas with the most Predictive Modeler job openings:
What are popular job titles related to Predictive Modeler jobs in TX? For Predictive Modeler jobs in TX, the most frequently searched job titles are:
Predictive Modeler jobs near you
Infographic showing various Predictive Modeler job openings in Texas as of June 2026, with employment types broken down into 95% Full Time, 3% Part Time, and 2% Nights. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $113,776 per year, or $54.7 per hour.

Data Scientist

Cliff Services Inc

Dallas, TX • On-site

Other

Posted 16 days ago

Job description

Role: Data Scientist

Location: Dallas, TX

Hybrid

Role Summary

Data Scientists bridge raw data and actionable business insights - building predictive models, running experiments, and communicating findings to both technical and non-technical stakeholders.

Key Responsibilities

Extract insights from large datasets to inform strategic decisions

Develop predictive models and ML algorithms to forecast trends

Identify patterns, anomalies, and opportunities for improvement

Enable data-driven decisions through analytics and visualization

Requirements

1-5 years in a data analyst, data scientist, or ML engineer role

Strong foundation in statistics, probability, and data modeling

Proficiency in Python, R, or SQL

Tech Stack

Category

Tools

Languages

Python, R, SQL

ML Libraries

Scikit-learn, TensorFlow, PyTorch

GenAI / LLMs

LangChain, OpenAI APIs, Hugging Face

MLOps

MLflow, Docker, Airflow

Cloud

AWS

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