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Machine Learning Data Associate Jobs in Porter, TX

Hp

Principal AI Data Scientist

Spring, TX · On-site

$147K - $230K/yr

Principal AI Data Scientist Description - About the Position The HP Enterprise AI & Machine Learning organization is a centralized team of data scientists and machine learning engineers building ...

Varsity Tutors

Data Science Tutor

Houston, TX · Remote

$40/hr

Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning, data visualization, SQL, Python or R programming, hypothesis testing, and communication of data ...

Marencor

Gen AI/ML Solution Architect

Houston, TX · On-site

$60.25 - $79.25/hr

The ideal candidate will have over a decade of expertise in AI, machine learning, data mining, NLP, and predictive analytics, with proven success in architecting large-scale data science solutions ...

Capgemini

Associate Data Scientist

Houston, TX · On-site

$56K - $56K/yr

Associate Data Scientist Location Houston TX Your Role Capgemini is seeking an enthusiastic and ... Foundational knowledge of Artificial Intelligence, Machine Learning, and Deep Learning concepts.

New

SwiftCruit

Data Scientist

Spring, TX · On-site

Basic knowledge of machine learning, data integration, and modeling skills and ETL tools (e.g. Informatica, Ab Initio, Talend). * Basic communication and presentation skills. * Basic data knowledge ...

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All JobsMachine Learning Data Associate JobsMachine Learning Data Associate Jobs in Porter, TX

Machine Learning Data Associate information

See Porter, TX salary details

$8

$17

$27

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

As of Sep 13, 2026, the average hourly pay for machine learning data associate in Porter, TX is $17.01, according to ZipRecruiter salary data. Most workers in this role earn between $13.94 and $18.12 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 near Porter, TX are hiring for Machine Learning Data Associate jobs?

Cities near Porter, TX with the most Machine Learning Data Associate job openings:

Machine Learning Data Associate jobs near you
Infographic showing various Machine Learning Data Associate job openings in Porter, TX as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 11% Part Time, and 4% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $35,381 per year, or $17 per hour.

Lead Data Scientist - Healthcare Analytics & Machine Learning

Houston, TX • Remote

MaxIT Consulting - Max Corporate Group
See more jobs at MaxIT Consulting - Max Corporate Groupexternal

Full-time

Posted 12 days ago

Key responsibilities

  • Lead high-priority data science and advanced analytics initiatives with organization-wide impact.

  • Analyze complex, large-scale structured and unstructured data sets using advanced statistical and analytical techniques.

  • Partner with cross-functional teams and internal stakeholders to identify business requirements and analytical opportunities.

Job description

Lead Data Scientist – Healthcare Analytics & Machine Learning

United States | Remote within GA, LA, OK, TN or TX | Direct Hire

The Opportunity

A large healthcare organization is seeking an experienced Lead Data Scientist to lead advanced analytics initiatives involving complex structured and unstructured data.

This role combines hands-on data science, statistical modeling, machine learning, stakeholder engagement, and technical leadership. The successful candidate will partner with cross-functional teams to translate complex business challenges into analytical solutions and deliver actionable insights that support data-driven decision-making.

The position reports to the Manager of Data Science and includes responsibility for leading high-priority projects, mentoring other data scientists, and presenting analytical findings to senior leadership.

Key Responsibilities
  • Lead high-priority data science and advanced analytics initiatives with organization-wide impact.
  • Analyze complex, large-scale structured and unstructured data sets using advanced statistical and analytical techniques.
  • Develop custom data models and algorithms to address business questions and improve operational performance.
  • Build and apply predictive models and analytical approaches to key business metrics.
  • Conduct research, statistical analysis, modeling, data mining, visualization, and pattern analysis.
  • Develop and test hypotheses and translate findings into clear, actionable recommendations.
  • Maintain existing analytical models and evaluate model performance and goodness of fit.
  • Partner with cross-functional teams and internal stakeholders to identify business requirements and analytical opportunities.
  • Identify, investigate, and resolve complex data quality and data availability issues.
  • Improve the efficiency, scalability, and reliability of data processes.
  • Manage multiple small and medium-sized analytical engagements and competing priorities.
  • Provide technical guidance, coaching, and mentoring to other data scientists.
  • Help educate broader audiences on data science capabilities, techniques, and developments.
  • Communicate complex analytical concepts to both technical and non-technical stakeholders.
  • Present analytical findings and recommendations to senior leadership.
  • Assist in evaluating data science tools, platforms, and vendors.
Required Qualifications
  • Bachelor's Degree in Science, Engineering, Computer Science, Mathematics, Statistics, or another related STEM discipline.
  • Minimum of 7 years of professional Data Science experience.
  • Strong business analytical capabilities, including process analysis, modeling, spreadsheets, procedures, and analytical problem-solving.
  • Strong understanding of data architecture and design principles.
  • Advanced analytical reasoning, problem-solving, and decision-making skills.
  • Demonstrated ability to independently investigate complex problems and identify the information necessary to reach sound conclusions.
  • Ability to manage multiple initiatives with competing priorities while meeting project goals and deadlines.
  • Excellent written and verbal communication skills.
  • Ability to explain complex technical and analytical information to both technical and business audiences.
  • Strong stakeholder management and client-facing capabilities.
  • Ability to work independently with minimal supervision in a fast-paced, multidisciplinary environment.
  • Strong ability to troubleshoot issues, recommend solutions, and manage challenging stakeholder situations.
Required Technical & Analytical Experience

Candidates should demonstrate strong practical knowledge of:

  • Machine learning techniques, including:
    • Clustering
    • Decision tree learning
    • Artificial neural networks
    • Understanding of the practical advantages and limitations of different modeling approaches
  • Advanced statistical techniques and concepts, including:
    • Regression
    • Statistical distributions
    • Statistical testing
    • Time series forecasting
    • A/B testing
    • Clustering
  • Predictive modeling and advanced analytics.
  • Data mining, visualization, and pattern analysis.
  • Advanced SQL and database management tools.
  • Programming for analytical and data science applications.
  • Statistical analysis tools.
  • The full data science project lifecycle.
  • Analysis of large, complex, and incomplete data sources.
  • Model evaluation and interpretation of analytical results.
Leadership & Stakeholder Management

The ideal candidate will be able to combine technical depth with strong business communication.

The role requires the ability to:

  • Translate complex data into meaningful business insights.
  • Gather requirements directly from stakeholders.
  • Build compelling, evidence-based data stories.
  • Present findings confidently to senior and executive leadership.
  • Lead cross-functional analytical initiatives.
  • Mentor and provide technical guidance to less experienced data science professionals.
  • Translate complex findings into clear recommendations for a broad range of stakeholders.
Preferred Experience

The following experience is preferred but not required:

  • Master's Degree in Data Science.
  • Professional experience within a hospital or healthcare environment.
  • Medical informatics.
  • Healthcare information technology.
  • Healthcare finance or revenue cycle data management.
  • Electronic Health Record (EHR) data management.
Candidate Profile

The strongest candidate will combine advanced quantitative expertise with strong business judgment and communication skills.

They should be comfortable moving from raw and incomplete data through statistical analysis and modeling, identifying meaningful insights, and ultimately presenting those findings in a concise and actionable manner to senior stakeholders.

A strong analytical mindset, executive-level communication capability, project ownership, and the ability to mentor others are important for success in this position.

Work Arrangement

This opportunity is remote, but candidates must be able to work from one of the following states:

  • Georgia
  • Louisiana
  • Oklahoma
  • Tennessee
  • Texas

Travel of up to 20% may be required.

Work Authorization

Some visa sponsorship arrangements may be supported for this opportunity. Eligibility should be evaluated based on the individual candidate's circumstances.