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Ml Data Associate Jobs in Texas (NOW HIRING)

Lantern

Data Scientist

Dallas, TX · On-site

Azure Data Scientist Associate), or Databricks ML Data Scientist Certifications a plus * Experience with GitHub or Azure DevOps * Prior consulting and business development experience a plus.

Lantern

Data Scientist

Dallas, TX · On-site

Azure Data Scientist Associate), or Databricks ML Data Scientist Certifications a plus * Experience with GitHub or Azure DevOps * Prior consulting and business development experience a plus.

Lantern

Data Scientist

Dallas, TX

Azure Data Scientist Associate), or Databricks ML Data Scientist Certifications a plus * Experience with GitHub or Azure DevOps * Prior consulting and business development experience a plus.

1 point system

Solution Architect

Plano, TX · On-site

$60.25 - $79.50/hr

AI-102 (Azure AI Engineer Associate), DP-100 (Azure Data Scientist Associate), or Databricks ML Data Scientist Certifications. Azure Solutions Architect

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All JobsMl Data Associate JobsMl Data Associate Jobs in Texas

Ml Data Associate information

See Texas salary details

$53.6K

$63.4K

$120.2K

How much do ml data associate jobs pay per year?

As of Jul 27, 2026, the average yearly pay for ml data associate in Texas is $63,389.00, according to ZipRecruiter salary data. Most workers in this role earn between $55,000.00 and $55,400.00 per year, depending on experience, location, and employer.

What is the salary of ML data operations associate?

The salary of an ML Data Associate typically ranges from $40,000 to $70,000 annually, depending on experience, location, and company size. Entry-level positions may start lower, while experienced professionals with specialized skills in data annotation and machine learning tools can earn higher salaries.

What are the key skills and qualifications needed to thrive as an ML Data Associate, and why are they important?

To thrive as an ML Data Associate, you need strong analytical skills, attention to detail, and a solid understanding of data annotation or labeling, often supported by a degree in a technical field. Familiarity with data labeling tools, basic programming (such as Python), and experience working with machine learning platforms are typically required. Excellent communication, problem-solving abilities, and the capacity to work efficiently in teams are important soft skills. These skills ensure high-quality, accurately labeled datasets that are essential for training effective machine learning models.

What are ML Data Associates?

ML Data Associates are professionals who support machine learning projects by preparing, labeling, and validating data used to train and evaluate algorithms. They often work with large datasets, ensuring data quality and accuracy, and may use specialized tools to annotate images, text, or audio. Their work is essential for enabling machine learning models to learn from high-quality, well-structured data, and they often collaborate with data scientists and engineers to optimize data pipelines.

What is the difference between Ml Data Associate vs Data Analyst?

AspectML Data AssociateData Analyst
Required CredentialsTypically a degree in computer science, data science, or related field; familiarity with machine learning conceptsUsually a degree in statistics, mathematics, or business analytics; strong Excel and data visualization skills
Work EnvironmentTech companies, AI startups, or organizations focusing on machine learning projectsBusiness, finance, marketing, and consulting firms analyzing data for insights
Employer & Industry UsageUsed in industries developing AI models, machine learning pipelines, and data infrastructureCommon across industries for reporting, trend analysis, and strategic decision-making

While both roles involve working with data, ML Data Associates focus on preparing and managing data specifically for machine learning models, whereas Data Analysts interpret data to generate business insights. The roles overlap in data handling skills but differ in their end goals and technical focus.

Is being an ML data associate stressful?

Working as an ML data associate can be stressful due to tight deadlines, repetitive tasks, and the need for high accuracy in data labeling and management. The role often requires attention to detail, patience, and the ability to handle large volumes of data efficiently.

Is ML a high paying job?

Machine Learning (ML) Data Associate roles typically offer competitive salaries that vary based on experience, location, and industry. Entry-level positions may start lower, but with skills in programming, data analysis, and familiarity with ML tools, salaries can increase significantly with experience and specialization.

How much does an ML Data Associate make?

An ML Data Associate typically earns between $40,000 and $70,000 annually, depending on experience, location, and the complexity of data tasks. Entry-level positions may start lower, while experienced associates with specialized skills in data annotation or labeling can earn higher salaries.

What are some common challenges faced by ML Data Associates when labeling complex datasets, and how can they be effectively addressed?

ML Data Associates often encounter challenges with ambiguous data, inconsistent labeling guidelines, or rapidly evolving project requirements. To address these, it's important to maintain open communication with data scientists and project leads, ask clarifying questions, and participate in regular calibration sessions to ensure consistency. Utilizing annotation tools efficiently and staying up-to-date with best practices can also help manage complexity and improve label quality. Collaboration and feedback within the team are key to overcoming these challenges and ensuring high-quality datasets.
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What cities in Texas are hiring for Ml Data Associate jobs? Cities in Texas with the most Ml Data Associate job openings:
Ml Data Associate jobs near you
Infographic showing various Ml Data Associate job openings in Texas as of July 2026, with employment types broken down into 1% As Needed, 70% Full Time, 26% Part Time, 1% Temporary, 1% Contract, and 1% Nights. Highlights an 97% Physical, 1% Hybrid, and 2% Remote job distribution, with an average salary of $63,389 per year, or $30.5 per hour.
Data Scientist

Data Scientist

Lantern

Dallas, TX • On-site

Other

Posted 13 days ago

Job description

As a Data Scientist, you will be responsible for assisting our clients envision, design, develop, and deploy machine learning solutions in Microsoft Azure. As part of a small, dynamic team, you will have the opportunity to contribute to multiple projects and multiple phases of the solution life cycle including solution design and implementation.
Key Responsibilities
  • Experience in the full ML lifecycle - understanding, developing, deploying, and maintaining traditional data science solutions.
  • Proficiency with Microsoft Azure technologies such as Azure Machine Learning and Azure Databricks.
  • Strong programming skills in Python or PySpark.
  • Solid understanding of supervised + unsupervised learning algorithms and concepts.
  • Experience with data preparation, feature engineering, and data engineering practices. Understanding of supervised + unsupervised learning algorithms and concepts.
  • Experience in the optimization and tuning of machine learning solutions to handle large volumes of data.
  • Outstanding verbal and written communication skills.
  • Excellent presentation and whiteboarding skills.
  • Experience communicating highly technical concepts to non-technical audiences. 
  • Experience collaborating with business stakeholders to understand business requirements and design AI solutions which meet those requirements.
Skills, Knowledge and Expertise
  • Bachelor's degree in computer science or related field
  • Experience building solutions with Azure AI Services (OpenAI, Vision, Speech, etc.), Microsoft Fabric or Azure Data Factory.
  • AI-102 (Microsoft Certified: Azure AI Engineer Associate), or DP-100 (Microsoft Certified: Azure Data Scientist Associate), or Databricks ML Data Scientist Certifications a plus 
  • Experience with GitHub or Azure DevOps 
  • Prior consulting and business development experience a plus.

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