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Model Predictive Control Jobs in Texas (NOW HIRING)

Predictive Analytics Engineer

Dallas, TX ยท On-site

$100K - $120K/yr

Opportunity for advancement Data Scientist / Predictive Analytics Engineer Location: Dallas, TX ... model deployment, and monitoring is a plus. * Familiarity with version control systems such as Git.

Services Principal Consultant

Houston, TX ยท Hybrid

$124K - $207K/yr

Understanding of Model Predictive Control (MPC) concepts and exposure to MPC solutions from multiple vendors. * Strong analytical and problem-solving skills, particularly in refining, oil & gas, and ...

Services Principal Consultant

Houston, TX ยท On-site

$124K - $207K/yr

Understanding of Model Predictive Control (MPC) concepts and exposure to MPC solutions from multiple vendors. * Strong analytical and problem-solving skills, particularly in refining, oil & gas, and ...

Experience with advanced process control and optimization, such as soft sensors, model predictive control, Bayesian optimization, and design of experiments. * Experience with deep learning frameworks ...

Experience with advanced process control and optimization, such as soft sensors, model predictive control, Bayesian optimization, and design of experiments. * Experience with deep learning frameworks ...

Predictive Forecasting: Formulate highly detailed cost forecasts for future project phases to drive ... Mastery of modern cost control methodologies, financial modeling, and variance analysis. * Advanced ...

Predictive Forecasting: Formulate highly detailed cost forecasts for future project phases to drive ... Mastery of modern cost control methodologies, financial modeling, and variance analysis. * Advanced ...

Design, build, and deploy predictive models and machine learning (ML) algorithms to support asset ... Use version control (e.g., Git), MLFlow and continuous integration/continuous deployment (CI/CD ...

New

... predictive modeling, anomaly detection, and utility analytics across every meter and system. For 13 ... Review control strategies and sequences of operation under guidance. * Analyze HVAC and BAS data to ...

... predictive modeling, anomaly detection, and utility analytics across every meter and system. For 13 ... Review control strategies and sequences of operation under guidance. * Analyze HVAC and BAS data to ...

Predictive Modeling: Build and maintain basic machine learning models (Regression, Random Forest ... Dockerized development, Git-based version control Qualifications Education: * Bachelor's degree (or ...

Entry Level Data Analyst

Austin, TX ยท On-site

$70 - $95/hr

Predictive Modeling: Build and maintain basic machine learning models (Regression, Random Forest ... Dockerized development, Git-based version control Qualifications Education * Bachelor's degree (or ...

Predictive Modeling: Build and maintain basic machine learning models (Regression, Random Forest ... Dockerized development, Git-based version control Qualifications Education: * Bachelor's degree (or ...

Predictive Modeling: Build and maintain basic machine learning models (Regression, Random Forest ... Dockerized development, Git-based version control Qualifications Education: * Bachelor's degree (or ...

Showing results 41-60

Model Predictive Control information

What is model predictive control?

Model Predictive Control (MPC) is an advanced method of process control that uses a mathematical model to predict and optimize the future behavior of a system. It works by solving an optimization problem at each control step to determine the best sequence of control actions, taking into account system constraints and objectives. MPC is widely used in industries such as chemical processing, energy, and automotive because it can handle multivariable control problems and anticipate future events. Its predictive nature allows for improved performance, stability, and efficiency compared to traditional control methods.

What are the typical challenges faced by engineers working with model predictive control systems in an industrial setting?

Engineers working with Model Predictive Control systems often encounter challenges related to model accuracy, computational demands, and real-time implementation. Ensuring the process model accurately represents the plant dynamics is critical, as discrepancies can lead to suboptimal control performance. Additionally, MPC algorithms can be computationally intensive, particularly for large-scale or fast processes, requiring careful tuning and optimization to maintain real-time operation. Collaboration with process engineers and IT specialists is common, as integrating MPC with existing control systems and plant infrastructure is a key part of the role.

What are the key skills and qualifications needed to thrive as a model predictive control engineer, and why are they important?

To thrive as a Model Predictive Control Engineer, you need strong foundations in control theory, applied mathematics, and process engineering, usually supported by a degree in engineering or a related field. Proficiency with simulation tools such as MATLAB/Simulink, programming languages like Python or C++, and familiarity with industrial automation systems are typically required. Analytical thinking, problem-solving abilities, and effective communication skills help distinguish top performers in this role. These skills are essential for designing, implementing, and optimizing advanced control algorithms that improve system performance and reliability in complex industrial environments.

What is the difference between Model Predictive Control vs Control Systems Engineer?

AspectModel Predictive ControlControl Systems Engineer
CredentialsEngineering degree, control theory, process modelingEngineering degree, control systems, automation
Work EnvironmentIndustrial automation, process control, manufacturingDesign, develop, and maintain control systems across industries
Industry UsageProcess industries, chemical, oil & gas, manufacturingAutomation, robotics, embedded systems, industrial sectors

Model Predictive Control (MPC) focuses on advanced control algorithms for optimizing processes, while Control Systems Engineers design and implement various control systems. MPC is a specialized skill within control engineering, often requiring knowledge of process modeling and optimization, whereas Control Systems Engineers have broader responsibilities across multiple control technologies. Both roles are essential in industrial automation but differ in scope and application.

What does a model predictive control do?

A Model Predictive Control (MPC) engineer designs control systems that use a mathematical model to predict future system behavior and optimize control actions accordingly. MPC is commonly used in industries like process control and robotics, requiring skills in control theory, programming, and system modeling. The role involves developing algorithms, tuning controllers, and ensuring system stability and efficiency.

What cities in Texas are hiring for Model Predictive Control jobs?

Cities in Texas with the most Model Predictive Control job openings:

Infographic showing various Model Predictive Control job openings in Texas as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution.

Predictive Analytics Engineer

Select Minds LLC

Dallas, TX โ€ข On-site

$100K - $120K/yr

Full-time

Posted 25 days ago


Job description

Benefits:
  • HYBRID
  • Competitive salary
  • Opportunity for advancement

Data Scientist / Predictive Analytics Engineer
Location: Dallas, TX (Hybrid, 3 days onsite per week)
Employment Type: Full-Time / Contract (W2)
Duration: Long-Term
Work Authorization: Open to candidates authorized to work in the U.S.
Interview Process: Video Interview followed by Client Interview

We are seeking a talented Data Scientist to join our growing analytics team in Dallas, TX.
The ideal candidate will have experience building predictive models, developing machine learning solutions, and transforming complex datasets into actionable business insights.
will work closely with product, engineering, and business stakeholders to drive data-driven decision making and improve business outcomes.
Key Responsibilities
* Collect, clean, and integrate structured and unstructured data from multiple sources.
* Build, train, validate, and deploy machine learning models for predictive analytics.
* Design and execute A/B testing and statistical experiments to optimize products and business processes.
* Develop automated dashboards and reports to monitor KPIs and business performance.
* Perform exploratory data analysis to identify trends, patterns, and opportunities.
* Present analytical findings and recommendations to technical and non-technical stakeholders.
* Collaborate with cross-functional teams including Product, Engineering, Marketing, and Business Operations.
* Optimize existing data science workflows and improve model performance.
* Ensure data quality, governance, and best practices throughout the analytics lifecycle.
Required Skills
* 2+ years of professional experience as a Data Scientist.
* Strong programming skills in Python or R.
* Advanced SQL skills with experience querying complex relational databases.
* Hands-on experience with machine learning frameworks such as:
* Scikit-Learn * TensorFlow * PyTorch
* Experience with statistical modeling, predictive analytics, and feature engineering.
* Strong understanding of:
* Regression Analysis * Hypothesis Testing * Probability & Statistics
* Experience with data visualization tools such as:
* Tableau * Power BI * Matplotlib
* Excellent analytical, problem-solving, and communication skills.
Preferred Qualifications
* Experience working with cloud platforms such as AWS, Azure, or GCP.
* Knowledge of data pipelines, ETL processes, and big data technologies.
* Experience with MLOps, model deployment, and monitoring is a plus.
* Familiarity with version control systems such as Git.
Education
* Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, Analytics, or a related quantitative field.
Why Join Us?
* Work on impactful machine learning and AI initiatives.
* Hybrid work environment in Dallas, TX.
* Collaborative, data-driven culture.
* Opportunity to work with modern analytics and cloud technologies.
* Competitive compensation and career growth opportunities.
Flexible work from home options available.
Compensation: $100,000.00 - $120,000.00 per year
About Us
We work to deliver profitability in your business - with effective communication, consulting, and interactive solutions. Following an Agile Work Approach, we make sure you get the ideal solutions at minimum expenses.
Work Approach
Our Philosophy
Our Philosophy starts-and-ends at the Client-first approach. Be it understanding your business requirements to choosing the right technologies, we work as a collective team that takes all the possible steps to grow continuously towards our common goal.
Work Policy
We promote a collaborative work environment. We involve everyone working in the organization in community decisions and encourage them to think from a broader perspective. Our work process promotes flexibility and we maintain a high level of discipline at different levels of execution.
The Future
SelectMinds have years of experience in the domain helps us understand the need-of-the-hour better. This understanding drives us to a better future with every minute ticking. We believe we will be taking off major businesses from their flagship positions, with the products we are eyeing today.