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Contract Machine Learning Data Scientist Jobs in Euless, TX

Highbrow LLC

Data Scientist / ML Engineer

Frisco, TX · On-site

$100 - $130/hr

Data Scientist / ML Engineer Year Of Experience : 7+ years Location: Overland Park KS/ Frisco TX ( ... Expertise with scaling pilot machine learning solutions to a large scale production environment ...

Judge Group, Inc.

Data Scientist - IV

Dallas, TX · On-site

Irving, TX (Hybrid) Duration: Long term contract Responsibilities: Independently work on data ... of machine learning/statistical models and ensure best performance Work closely with machine ...

Select Minds LLC

Data Scientist

Dallas, TX · On-site

$65 - $75/hr

Roles & Responsibilities . 6+ years of experience in Machine Learning and Data Science. * Strong understanding of Generative AI, Retrieval Augmented Generation, Agentic Workflow, Statistical methods ...

Ruri Software Technologies LLC

Data Scientist

Plano, TX · On-site

Data Scientist Location : Plano, TX, 5900 West Plano Parkway, 75093 About the Role We're looking ... Apply AI and machine learning to improve operations and decision-making * Partner with business and ...

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All JobsContract Machine Learning Data Scientist JobsContract Machine Learning Data Scientist Jobs in Euless, TX

Contract Machine Learning Data Scientist information

See Euless, TX salary details

$34.7K

$113.6K

$181.8K

How much do contract machine learning data scientist jobs pay per year?

As of Aug 30, 2026, the average yearly pay for contract machine learning data scientist in Euless, TX is $113,572.00, according to ZipRecruiter salary data. Most workers in this role earn between $91,100.00 and $125,800.00 per year, depending on experience, location, and employer.

What is a contract machine learning data scientist?

A Contract Machine Learning Data Scientist is a professional who works on a temporary or project-based basis to build, implement, and optimize machine learning models for organizations. Unlike full-time employees, contract data scientists are hired for specific projects or timeframes and may work independently or as part of a team. Their responsibilities typically include data cleaning, feature engineering, model selection, and communicating insights to stakeholders. Contract roles offer flexibility for both the professional and the employer, often focusing on specialized tasks or filling short-term skill gaps.

What are the key skills and qualifications needed to thrive as a contract machine learning data scientist?

To excel as a Contract Machine Learning Data Scientist, you need a strong background in statistics, programming (Python/R), and applied machine learning, typically supported by a relevant degree in computer science, mathematics, or a related field. Familiarity with tools and frameworks such as TensorFlow, PyTorch, scikit-learn, cloud platforms (AWS, GCP, Azure), and version control systems is essential, along with experience deploying models in production. Exceptional problem-solving abilities, communication skills, and adaptability help you translate business needs into actionable data solutions and quickly integrate into new teams. These skills are crucial for delivering high-impact, reliable machine learning solutions on tight project timelines and in diverse organizational environments.

How do contract machine learning data scientists typically collaborate with in-house teams during a project?

Contract machine learning data scientists often work closely with in-house data teams, product managers, and engineers to align project goals and deliverables. They frequently participate in virtual meetings, code reviews, and regular progress updates to ensure transparency and seamless integration of their work. Effective communication and documentation are critical, as contractors may need to quickly adapt to the company's workflows and tools. This collaborative environment enables contractors to contribute specialized expertise while staying attuned to the broader objectives of the organization.

What is the difference between Contract Machine Learning Data Scientist vs Contract Data Scientist?

AspectContract Machine Learning Data ScientistContract Data Scientist
CredentialsTypically requires advanced degrees in data science, machine learning, or related fieldsRequires similar degrees but may have a broader focus on data analysis
Work EnvironmentOften in tech, finance, or healthcare industries focusing on ML projectsVaries across industries, including marketing, finance, and consulting
Employer UsageUsed by companies developing AI/ML solutions or productsEmployed for data analysis, reporting, and strategic insights
Search & Comparison IntentOften searched by those interested in AI/ML-specific rolesMore general, related to data analysis roles

The main difference is that Contract Machine Learning Data Scientists focus on developing and implementing machine learning models, while Contract Data Scientists may handle broader data analysis tasks without necessarily specializing in ML. Both roles require strong analytical skills and relevant credentials, but their project focus and industry applications differ.

What are popular job titles related to Contract Machine Learning Data Scientist jobs in Euless, TX?

For Contract Machine Learning Data Scientist jobs in Euless, TX, the most frequently searched job titles are:

What cities near Euless, TX are hiring for Contract Machine Learning Data Scientist jobs?

Cities near Euless, TX with the most Contract Machine Learning Data Scientist job openings:

Contract Machine Learning Data Scientist jobs near you

Data Scientist Architect

Mars Technominds Inc

Garland, TX • On-site

Other

Posted 2 days ago

New

Job description

Job Title: Data Scientist Architect

Location: Garland, TX / McKinney, TX

Duration: 12+ Months

Type: Long-Term Contract

Position Overview:

We are seeking an experienced Data Scientist Architect to design and lead advanced data science, machine learning, and AI solutions across enterprise environments. The ideal candidate will have a strong combination of data science, machine learning, data architecture, cloud platforms, and AI/ML engineering experience.

The Data Scientist Architect will work closely with business stakeholders, data engineers, software engineers, and technology leadership to define data and AI strategies, develop scalable analytical solutions, and drive machine learning initiatives from concept through production.

Key Responsibilities:

  • Design and architect scalable data science, machine learning, and AI solutions aligned with business objectives.
  • Lead the development and implementation of advanced machine learning and predictive analytics solutions.
  • Translate complex business problems into data-driven analytical and machine learning solutions.
  • Design end-to-end data science architectures covering data ingestion, processing, feature engineering, model development, deployment, and monitoring.
  • Collaborate with Data Engineers, ML Engineers, Software Engineers, and business stakeholders to deliver production-ready solutions.
  • Develop and optimize machine learning models using structured and unstructured data.
  • Establish best practices for model development, validation, deployment, monitoring, and lifecycle management.
  • Design and implement MLOps processes and frameworks for automated model deployment and monitoring.
  • Work with large-scale datasets and develop solutions for data preparation, transformation, feature engineering, and statistical analysis.
  • Evaluate and implement appropriate machine learning algorithms and AI technologies based on business requirements.
  • Develop solutions using Python and modern data science/ML frameworks.
  • Design and integrate data science solutions with enterprise data platforms, APIs, and applications.
  • Collaborate with cloud teams to develop scalable AI/ML solutions using AWS, Azure, and/or Google Cloud.
  • Establish data quality, governance, security, and model risk management practices.
  • Perform exploratory data analysis and communicate insights and recommendations to technical and business stakeholders.
  • Provide technical leadership, architectural guidance, and mentorship to data science and engineering teams.
  • Stay current with emerging technologies in AI, Generative AI, Machine Learning, Deep Learning, and Data Engineering.

Required Technical Skills:

  • Strong experience in Data Science and Data Science Architecture.
  • Advanced Python programming skill
  • Strong knowledge of Machine Learning, Statistical Modeling, Predictive Analytics, and Data Mining.
  • Experience with ML frameworks such as Scikit-learn, TensorFlow, PyTorch, XGBoost, or similar.
  • Strong understanding of data architecture, data pipelines, ETL/ELT, and data processing.
  • Experience with SQL and relational/non-relational databases.
  • Hands-on experience with cloud-based data and AI platforms.
  • Strong understanding of MLOps, model deployment, model monitoring, and ML lifecycle management.
  • Experience with distributed data processing technologies such as Spark/PySpark.
  • Experience with data visualization and analytical tools such as Power BI, Tableau, or similar.
  • Strong understanding of APIs, microservices, data integration, and enterprise architecture.

Preferred Skills:

  • Experience with Generative AI, Large Language Models (LLMs), NLP, or Deep Learning.
  • Experience with Azure Machine Learning, AWS SageMaker, Google Vertex AI, or equivalent platforms.
  • Experience with Databricks and modern cloud data platforms.
  • Knowledge of Vector Databases, RAG, embeddings, and AI application architecture.
  • Experience implementing CI/CD pipelines for machine learning solutions.
  • Knowledge of data governance, security, privacy, and compliance requirements.
  • Experience working with large-scale enterprise data environments.
  • Strong communication, presentation, problem-solving, and stakeholder-management skills.

Education & Experience:

  • Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field.
  • 8+ years of experience in Data Science, Machine Learning, Data Engineering, or related technology roles.
  • Demonstrated experience designing and delivering enterprise-scale data science and AI/ML solutions.
  • Proven ability to provide technical leadership and work across business and technology teams.

Apply