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Machine Learning Data Associate Jobs in Texas (NOW HIRING)

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 ...

The role involves developing and optimizing machine learning models, managing large-scale datasets ... Oversee data collection, preprocessing, and augmentation to maintain high-quality datasets for ...

As a Data Scientist, you will apply strong expertise through the use of machine learning, data mining, and information retrieval to design, prototype, and build next generation advanced analytics ...

As a Performance Assurance Machine Learning Engineer, you will work under the coaching of Senior ... You will utilize skills to query databases to extract data, use skills in Python or R to analyze ...

As a Performance Assurance Machine Learning Engineer, you will work under the coaching of Senior ... You will utilize skills to query databases to extract data, use skills in Python or R to analyze ...

Machine Learning Engineer

Austin, TX · On-site

$100 - $130/hr

... data-driven decisions • Develop scalable machine learning pipelines and systems • Maintain up-to-date knowledge of emerging AI and machine learning trends • Ensure the quality and performance ...

Showing results 41-60

Machine Learning Data Associate information

See Texas salary details

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$17

$28

How much do machine learning data associate jobs pay per hour?

As of Aug 20, 2026, the average hourly pay for machine learning data associate in Texas is $17.46, according to ZipRecruiter salary data. Most workers in this role earn between $14.33 and $18.61 per hour, depending on experience, location, and employer.

What is a machine learning data associate?

Machine Learning Data Associates are professionals who support the development of machine learning models by preparing, labeling, and validating data sets. Their work ensures that data used for training algorithms is accurate, consistent, and properly annotated. They may also assist with data cleaning, quality checks, and sometimes basic data analysis tasks. This role is crucial in industries where high-quality labeled data is essential for building effective AI systems.

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

To thrive as a Machine Learning Data Associate, you need strong analytical skills, attention to detail, and a basic understanding of data annotation and labeling processes, often supported by a degree in computer science or a related field. Familiarity with data management tools, annotation platforms, and sometimes scripting languages like Python is typically required. Strong communication, collaboration, and problem-solving abilities help you work efficiently with data science teams and ensure high-quality outcomes. These skills and qualities are crucial for producing accurate datasets that directly impact the effectiveness of machine learning models.

How does a machine learning data associate typically collaborate with data scientists and engineers within a project team?

As a Machine Learning Data Associate, you play a vital role in supporting data scientists and engineers by annotating, cleaning, and organizing large datasets to ensure high data quality. You'll frequently communicate with team members to clarify labeling guidelines, provide feedback on data inconsistencies, and report any edge cases encountered during annotation. This collaboration ensures that the datasets used for training machine learning models are accurate and comprehensive, directly impacting the success of the project. Expect regular team meetings and ongoing feedback loops to maintain alignment with evolving project requirements.

What is the difference between Machine Learning Data Associate vs Data Analyst?

AspectMachine Learning Data AssociateData Analyst
Required SkillsData cleaning, labeling, basic programming, understanding of ML workflowsData interpretation, visualization, statistical analysis
Work EnvironmentTech companies, AI startups, research labsBusiness, finance, marketing, healthcare sectors
Common CertificationsData Science certifications, Python, SQLExcel, Tableau, SQL certifications

The main difference is that Machine Learning Data Associates focus on preparing and labeling data specifically for machine learning models, while Data Analysts interpret data to generate insights for business decisions. Both roles require strong data skills and often overlap, but their primary objectives and work environments differ.

How do I become a machine learning data associate?

To become a machine learning data associate, candidates typically need a high school diploma or equivalent, with some roles preferring a bachelor's degree in computer science, data science, or related fields. Relevant skills include data annotation, understanding of machine learning concepts, and proficiency with tools like Excel, SQL, or data labeling platforms. Gaining experience through internships or certifications can improve job prospects in this field.

Is a Machine Learning Data Associate a good job?

A Machine Learning Data Associate role involves preparing and managing data for machine learning models, often requiring skills in data cleaning, annotation, and familiarity with tools like Python or SQL. It can be a good entry-level position for those interested in AI and data science, offering opportunities to develop technical skills and gain industry experience. Compensation and job satisfaction vary depending on the employer and location, but it generally provides a solid foundation for a career in machine learning or data analysis.

What cities in Texas are hiring for Machine Learning Data Associate jobs?

Cities in Texas with the most Machine Learning Data Associate job openings:

Infographic showing various Machine Learning Data Associate job openings in Texas as of August 2026, with employment types broken down into 67% Full Time, 11% Part Time, 11% Contract, and 11% Nights. Highlights an 100% In-person job distribution, with an average salary of $36,310 per year, or $17.5 per hour.

Data Scientist / ML Engineer

Highbrow LLC

Frisco, TX • On-site

$100 - $130/hr

Other

Posted 14 days ago


Job description

Data Scientist / ML Engineer

Year Of Experience: 7+ years

Location: Overland Park KS/ Frisco TX ( 5 days onsite from day 1)

Visa Type :- (US Citizen only ) (Female candidate only required )

Employment Type :- W2

Duration :- Long Term

Job Description :-

7plus years of experience in statistical modeling, data mining, analytics techniques, machine learning software development and reporting

3plus years of applied experience in building and deploying Machine Learning solutions using various supervised/unsupervised ML algorithms such as Linear/Logistic Regression, Support Vector Machines, (Deep) Neural Networks, Random Forest, etc., and key parameters that affect their performance.

3plus years of hands-on experience with Python and/or R programming and statistical packages, and ML libraries such as scikit-learn, TensorFlow, PyTorch, etc.

3 plus years of experience in building use cases / solutions especially around AI/ML cognitive services, based on Cloud infrastructure and services such as Azure cloud platforms and On- premise environments

Expertise with SQL, noSQL, Python, R, Javascript programming languages and big data environments (such as Splunk, Hadoop, Spark, Flink, Stream Analytics, Kafka, Docker, Kubernetes etc.)

Experience developing experimental and analytic plans for data modeling processes, using strong baselines, and determining cause and effect relations.

Understanding of relevant statistical measures such as confidence intervals, significance of error measurements, development and evaluation data sets, etc. in data analysis projects.

Expertise with scaling pilot machine learning solutions to a large scale production environment

Expertise with visualization tools such as PowerBI, D3JS etc.

Excellent written and verbal communication skills.

Proficient in machine learning data workflows, data collection methodologies, and data analysis.

Experience with architecting, designing, developing software solution in Azure and on-prem

environments.

Certifications AI / ML and Azure Cloud platforms will be plus

Education:

  • Bachelor’s or Master’s degree in Computer Science, Computer or Electrical Engineering, Mathematics, or a related field.
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