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Predictive Modeling Jobs in Texas (NOW HIRING)

Lendistry

Data Scientist I

Dallas, TX · On-site

... predictive modeling. • Mine internal and external datasets to surface actionable insights into customer behavior, usage patterns, and risk indicators. • Own analytics projects end-to-end from ...

Atmosphere TV

Senior Data Scientist

Austin, TX

Predictive Venue Modeling & Contextual Enrichment * Build models that predict a venue's intrinsic revenue potential, enabling us to prioritize prospective venues for acquisition as well as flag under ...

Service Experts

Lead Data Analyst

Richardson, TX · On-site

Model Development & Enhancement: Provide prescriptive and predictive analytics expertise to support stakeholders in identifying opportunity areas, building robust models, and deploying data-driven ...

Service Experts

Sr. Data Analyst

Richardson, TX · On-site

$78K - $98K/yr

Model Development & Enhancement: Provide prescriptive and predictive analytics expertise to support stakeholders in identifying opportunity areas, building robust models, and deploying data-driven ...

Service Experts

Sr. Data Analyst

Richardson, TX · On-site

$78K - $98K/yr

Model Development & Enhancement: Provide prescriptive and predictive analytics expertise to support stakeholders in identifying opportunity areas, building robust models, and deploying data-driven ...

Credit Union of Texas

Data Scientist

Allen, TX

Use predictive modeling to increase and optimize member experiences, revenue generation, ad targeting and other business outcomes. Develop company A/B testing framework and test model quality.

Credit Union of Texas

Data Scientist

Allen, TX

Use predictive modeling to increase and optimize member experiences, revenue generation, ad targeting and other business outcomes. Develop company A/B testing framework and test model quality.

Service Experts

Lead Data Analyst

Richardson, TX · On-site

Model Development & Enhancement: Provide prescriptive and predictive analytics expertise to support stakeholders in identifying opportunity areas, building robust models, and deploying data-driven ...

Soni Resources

Data Engineer/Data Scientist

Houston, TX · On-site

$100/hr

This role builds the infrastructure and analytics models that convert raw data into actionable insights - supporting business intelligence, predictive modeling, and strategic initiatives across ...

Atmosphere TV

Senior Data Scientist

Austin, TX · On-site

Predictive Venue Modeling & Contextual Enrichment * Build models that predict a venue's intrinsic revenue potential, enabling us to prioritize prospective venues for acquisition as well as flag under ...

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How much do predictive modeling jobs pay per hour?

As of Jul 24, 2026, the average hourly pay for predictive modeling 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.

What is the highest paying modeling job?

In predictive modeling, senior data scientists and machine learning engineers typically earn the highest salaries, often exceeding six figures annually. These roles require advanced skills in statistical analysis, programming, and experience with tools like Python or R, and they are often found in industries such as finance, technology, and healthcare.

What are the key skills and qualifications needed to thrive in the Predictive Modeling position, 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 is a Predictive Modeling job?

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 is a predictive modeler?

A predictive modeler is a professional who develops statistical and machine learning models to forecast future outcomes based on historical data. They use tools like Python, R, or SAS and often require strong analytical skills and knowledge of data science techniques. Their work supports decision-making in various industries such as finance, marketing, and healthcare.

Is 40 too late for data science?

Predictive modeling is a key role in data science, and age is not a barrier to entering the field. Many professionals transition into data science later in their careers by developing skills in programming, statistics, and tools like Python or R, often through online courses or certifications. Success depends on your ability to learn and apply relevant skills, regardless of age.

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 jobs will no longer exist in 2030?

Predictive modeling roles may decline as automation and AI tools increasingly handle data analysis and forecasting tasks. Jobs that involve routine, repetitive tasks are also at risk of automation, potentially reducing demand for certain administrative or manual roles. However, new jobs may emerge in AI oversight, data ethics, and advanced analytics.
What are the most commonly searched types of Predictive Modeling jobs in Texas? The most popular types of Predictive Modeling jobs in Texas are:
What are popular job titles related to Predictive Modeling jobs in Texas? For Predictive Modeling jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Predictive Modeling jobs in Texas look for? The top searched job categories for Predictive Modeling jobs in Texas are:
What cities in Texas are hiring for Predictive Modeling jobs? Cities in Texas with the most Predictive Modeling job openings:
Predictive Modeling jobs near you
Infographic showing various Predictive Modeling job openings in Texas as of July 2026, with employment types broken down into 70% Full Time, 12% Part Time, and 18% Contract. Highlights an 67% Physical, 3% Hybrid, and 30% Remote job distribution, with an average salary of $113,776 per year, or $54.7 per hour.
Data Scientist I

Data Scientist I

Lendistry

Dallas, TX • On-site

Full-time

Posted 19 days ago

Job description

Job Summary:
Lendistry is the nation’s largest minority-led lender for small businesses and commercial real estate. The Data Scientist I will support the management and implementation of strategies on the decision-making platform, utilizing data-driven insights to shape business strategy and product development decisions.
Responsibilities:
• Implement, optimize, and monitor risk, fraud, line assignment, and pricing strategies within the decision engine across all lending channels, proactively identifying and resolving performance issues before they impact operations.
• Aggregate, structure, and analyze large-scale datasets using big data technologies to support credit risk modeling, fraud detection, and loss mitigation strategies.
• Develop and apply advanced statistical models and machine learning techniques to improve decision accuracy and risk management outcomes.
• Design scalable pipelines that transform raw, unstructured data into clean features for predictive modeling.
• Mine internal and external datasets to surface actionable insights into customer behavior, usage patterns, and risk indicators.
• Own analytics projects end-to-end from tool customization to building new analytical solutions while maintaining data integrity and pipeline reliability.
• Build and maintain tracking, monitoring, and reporting frameworks to measure the performance and impact of models, rules, and risk initiatives.
• Research and develop new methodologies and techniques to continuously improve the effectiveness of credit and fraud risk strategies.
• Partner with engineering, product, and business teams to align data science solutions with organizational goals and deliver measurable impact.
Qualifications:
Required:
• Bachelor's degree in a quantitative field (engineering, math, statistics, or similar).
• 3+ years of hands-on experience in business analysis, customer segmentation, and/or predictive modeling, preferably in the financial services industry.
• Proficiency in Python, SQL, and one or more additional scripting or programming languages (Java, SAS, etc.).
• Solid understanding of machine learning and statistical modeling techniques including logistic regression, gradient boosting (GBM), and clustering.
• Comfortable working with large datasets and translating complex analysis into clear, actionable outputs.
• Strong written and verbal communication skills; able to present findings clearly to both technical and non-technical audiences.
• Collaborative team player who can also work independently and manage competing priorities.
• Creative, analytical thinker with a bias toward action and continuous improvement.
Preferred:
• MS/PhD preferred.
• Experience implementing credit strategies within a decision engine platform (Provenir, GDS-Link, Zoot, or similar) is a strong plus.
Company:
Lendistry is a lender and fintech company that provides business loans and grant access to small businesses. Founded in 2015, the company is headquartered in Los Angeles, USA, with a team of 201-500 employees. The company is currently Growth Stage.

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