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Temporary Machine Learning R Jobs in Texas (NOW HIRING)

Tihinsurance

Machine Learning Engineer

Dallas, TX · On-site

Regular or Temporary: Regular Language Fluency: English (Required) Work Shift: 1st Shift (United States of America) Please review the following We are building the foundation of the machine learning ...

Highbrow LLC

Data Scientist / ML Engineer

Frisco, TX · On-site

$100 - $130/hr

... or R programming and statistical packages, and ML libraries such as scikit-learn, TensorFlow ... Expertise with scaling pilot machine learning solutions to a large scale production environment ...

New

IT America Inc

ML Engineer

Plano, TX · On-site

Develop and optimize machine learning and deep learning models using frameworks like TensorFlow or PyTorch. * Strong skills in programming languages such as Python, R, or Java, essential for ...

Techatix Corp.

Data Scientist

Austin, TX · On-site

$147.75 - $210.43/hr

Proficiency in Python, R, or similar programming languages. * Experience with machine learning frameworks (e.g., TensorFlow, PyTorch). * Strong statistical analysis and data visualization skills.

New

SwiftCruit

Staff Software Engineer - AI

Austin, TX · On-site

$180 - $240/hr

Experience with data science and machine learning tools (R, Python, Tensorflow, Spark). * Deep understanding of cloud-based networking. * Experience using Big Data technologies like Spark, Hive etc.

New

Cloudera

Staff Software Engineer - AI

Austin, TX · Hybrid

Experience with data science and machine learning tools (R, Python, Tensorflow, Spark) * Deep understanding of cloud-based networking * Experience using Big Data technologies like Spark, Hive etc.

Cloudera

Staff Software Engineer - AI

Austin, TX · Hybrid

Experience with data science and machine learning tools (R, Python, Tensorflow, Spark) * Deep understanding of cloud-based networking * Experience using Big Data technologies like Spark, Hive etc.

PROLIM Global Corporation

Data Scientist

Plano, TX · On-site

Proficiency in Python, R, and SQL. Mathematics/Statistics: Strong understanding of statistical techniques, probability, and linear algebra. Machine Learning: Knowledge of algorithms and libraries ...

Noblesoft Technologies

Lead Earnix developer

Plano, TX · On-site

Machine learning concepts * Data visualization * Proficiency in: * SQL * Python or R * Excel * Tableau / Power BI Key Responsibilities * Develop, maintain, and optimize pricing and predictive models ...

FreedomPay

Data Science Engineer

Austin, TX · On-site

$113K - $136K/yr

The role involves developing machine learning models, collaborating with various teams, and ... in Python, R, or similar statistical programming languages • Experience with techniques in ...

Cloudera

Staff Software Engineer - AI

Austin, TX · On-site

$140 - $190/hr

Experience with data science and machine learning tools (R, Python, Tensorflow, Spark)* Deep understanding of cloud-based networking* Experience using Big Data technologies like Spark, Hive etc.

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All JobsMachine Learning R JobsTemporary Machine Learning R JobsTemporary Machine Learning R Jobs in Texas

Temporary Machine Learning R information

What is the difference between Temporary Machine Learning R vs Data Analyst?

AspectTemporary Machine Learning RData Analyst
Required SkillsProficiency in R, machine learning algorithms, statistical modelingData visualization, SQL, basic statistical analysis
Work EnvironmentProject-based, technical teams, research-focusedBusiness units, reporting, data cleaning
CertificationsR programming, data science certificationsNone specific, often business or analytics certifications

Temporary Machine Learning R roles focus on developing predictive models using R and machine learning techniques, often in research or technical environments. Data Analysts typically handle data cleaning, visualization, and reporting for business insights. While both roles require analytical skills, Temporary Machine Learning R positions demand specialized knowledge in machine learning and R programming, making them more technical and research-oriented.

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Temporary Machine Learning R jobs near you
Infographic showing various Temporary Machine Learning R job openings in Texas as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Sr. Principal Data Scientist / Machine Learning Engineer

Ascentt

Plano, TX • On-site

Full-time

Re-posted yesterday

Job description

Ascentt is building cutting-edge data analytics & AI/ML solutions for global automotive and manufacturing leaders. We turn enterprise data into real-time decisions using advanced machine learning and GenAI. Our team solves hard engineering problems at scale, with real-world industry impact. We're hiring passionate builders to shape the future of industrial intelligence.
Job Summary
We're looking for an exceptionally skilled and experienced Sr. Principal Data Scientist / Machine Learning Engineer to lead and deliver high-impact AI/ML projects across Automotive domain. The ideal candidate will have a deep understanding of data science and machine learning tools, techniques, and algorithms, coupled with a proven track record of successfully leading projects from conception to deployment. This role demands strong client-facing communication skills and the ability to translate complex technical concepts into tangible business value.
Key Responsibilities
  • Technical Leadership & Strategy:
  • Serve as a primary technical expert and thought leader in Data Science and Machine Learning.
  • Define and drive the technical strategy for AI/ML initiatives, identifying high-value opportunities for optimization, predictive analytics, and process improvement across diverse use cases.
  • Architect and oversee the development of robust, scalable, and production-ready DS/ML models and solutions.
  • Stay at the forefront of the latest advancements in DS/ML, especially those applicable to various industries and large-scale data problems.
  • Project Leadership & Delivery:
  • Lead end-to-end DS/ML projects, including requirements gathering, data exploration, model development, validation, deployment, and monitoring.
  • Define project scope, timelines, and deliverables, ensuring successful execution within budget and schedule constraints.
  • Mentor and guide junior and mid-level data scientists and ML engineers, fostering a culture of technical excellence and continuous learning.
  • Drive MLOps best practices for reliable and efficient model deployment and lifecycle management.
  • Client Management & Communication:
  • Act as a trusted advisor to clients and internal stakeholders, understanding their business challenges and translating them into solvable DS/ML problems.
  • Effectively communicate complex analytical findings, model performance, and business recommendations to both technical and non-technical audiences.
  • Manage client expectations, present progress reports, and ensure stakeholder satisfaction.
  • Facilitate workshops and discovery sessions to identify new opportunities for AI/ML adoption.
  • Use Case Development & Problem Solving:
  • Lead the identification, prioritization, and execution of complex AI/ML use cases that drive significant business impact.
  • Apply deep analytical skills to dissect complex problems, derive actionable insights from data, and design innovative solutions.
  • Develop and implement models for:
  • Predictive Analytics: Forecasting, risk assessment, and anomaly detection.
  • Optimization: Improving efficiency, resource allocation, and decision-making.
  • Pattern Recognition: Identifying trends, segments, and relationships within large datasets.
  • Automation: Leveraging ML for intelligent process automation and enhanced operational efficiency.
  • Tool & Algorithm Proficiency:
  • Demonstrated expertise in a wide range of DS/ML tools and platforms (e.g., Python, R, TensorFlow, PyTorch, scikit-learn, Spark, AWS Sagemaker, Azure ML).
  • Deep understanding and practical application of various machine learning algorithms (e.g., supervised, unsupervised, reinforcement learning, deep learning, time series analysis, NLP, computer vision).
  • Proficiency in data manipulation, SQL, and working with large, complex datasets from various sources.

Qualifications
  • Master's or Ph.D. in Data Science, Machine Learning, Computer Science, Engineering, Operations Research, Statistics, or a related quantitative field.
  • 8+ years of progressive experience in Data Science and Machine Learning roles, with at least 3-5 years in a leadership or principal-level capacity.
  • Demonstrated experience leading multiple end-to-end DS/ML projects successfully from concept to production.
  • Proven track record of managing client interactions, presenting technical solutions, and influencing strategic decisions.
  • Expertise in Python programming (NumPy, Pandas, Scikit-learn, Keras/TensorFlow/PyTorch).
  • Strong understanding of statistical modeling, experimental design, and hypothesis testing.
  • Experience with cloud platforms (AWS, Azure, GCP) and MLOps principles.
  • Excellent communication, interpersonal, and presentation skills.

Preferred Qualifications
  • Experience with real-time data processing and streaming analytics.
  • Knowledge of various industry verticals and their unique data challenges (e.g., finance, healthcare, retail, logistics, manufacturing).
  • Experience with large-scale data architectures (e.g., data lakes, data warehouses, distributed computing).
  • Publications or presentations in relevant fields.

Apply