1

Freelance Machine Learning Data Annotation Jobs in Dallas, TX

Machine learning + Spark/Hive/SQL + Python, Scala, SQL PySpark, Kafka, use of scheduling tools ... Develop and implement data pipelines and Client Pipelines to facilitate model inference (both Real ...

Apply expertise in data mining and machine learning techniques, including forecasting, prediction, segmentation, recommendation, and fraud detection. Data Engineering and Preparation * Extend and ...

Machine Learning Engineer - NJ

Addison, TX · On-site

$54 - $71.50/hr

Apply expertise in data mining and machine learning techniques, including forecasting, prediction, segmentation, recommendation, and fraud detection. Data Engineering and Preparation: * Extend and ...

Data Scientist

Richardson, TX · Remote

$116K - $198K/yr

Machine Learning & Data Science * Develop, evaluate, and deploy predictive and generative models for real production use cases * Perform feature engineering and data preparation for modeling ...

Machine Learning Engineer - NJ

Addison, TX

$54 - $71.50/hr

Apply expertise in data mining and machine learning techniques, including forecasting, prediction, segmentation, recommendation, and fraud detection. Data Engineering and Preparation: * Extend and ...

Data Scientist

Richardson, TX · On-site

$116K - $198K/yr

Responsibilities Machine Learning & Data Science * Develop, evaluate, and deploy predictive and generative models for real production use cases * Perform feature engineering and data preparation for ...

Data Scientist

Richardson, TX · Remote

$116K - $198K/yr

Responsibilities Machine Learning & Data Science * Develop, evaluate, and deploy predictive and generative models for real production use cases * Perform feature engineering and data preparation for ...

Guides students through data preprocessing, feature selection, building and comparing ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Guides students through data preprocessing, feature selection, building and comparing ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Guides students through data preprocessing, feature selection, building and comparing ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Guides students through data preprocessing, feature selection, building and comparing ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Guides students through data preprocessing, feature selection, building and comparing ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

We're enhancing our applications with cloud-native capabilities, including data at scale, edge ... As an Machine Learning AI Development Manager for the AEC Solutions group, you will lead your team ...

New

Guides students through data preprocessing, feature selection, building and comparing ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Guides students through data preprocessing, feature selection, building and comparing ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

next page

Showing results 1-20

Freelance Machine Learning Data Annotation information

See Dallas, TX salary details

$12

$21

$34

How much do freelance machine learning data annotation jobs pay per hour?

As of Jun 13, 2026, the average hourly pay for freelance machine learning data annotation in Dallas, TX is $21.63, according to ZipRecruiter salary data. Most workers in this role earn between $17.12 and $24.71 per hour, depending on experience, location, and employer.

What is the difference between Freelance Machine Learning Data Annotation vs Data Labeler?

AspectFreelance Machine Learning Data AnnotationData Labeler
CredentialsBasic understanding of annotation tools, sometimes with specialized domain knowledgeTypically no formal credentials required
Work EnvironmentRemote, flexible, project-basedOften remote or in-house, depending on employer
Industry UsageUsed in AI/ML development for training datasetsUsed in data preparation for various industries, including AI
Search/Comparison IntentFocuses on freelance opportunities, project scope, and toolsMore general, often employed by companies for data labeling tasks

Freelance Machine Learning Data Annotation involves independently completing annotation tasks for AI models, often with specialized tools and domain knowledge. Data Labelers typically perform similar tasks but may work as employees or contractors within a company. The main difference lies in the freelance nature and project-based work of data annotation roles.

What are the key skills and qualifications needed to thrive as a Freelance Machine Learning Data Annotation specialist, and why are they important?

To thrive as a Freelance Machine Learning Data Annotation specialist, you need attention to detail, basic knowledge of data labeling concepts, and familiarity with machine learning data types. Experience with annotation tools (such as Labelbox, RectLabel, or CVAT) and understanding of data privacy protocols are commonly required. Strong communication, time management, and the ability to follow complex guidelines are essential soft skills for delivering accurate results. These skills ensure high-quality, consistent data annotation, which is critical for effective machine learning model training and performance.

What is freelance machine learning data annotation?

Freelance machine learning data annotation involves labeling or tagging data—such as images, text, audio, or video—to help train machine learning models. As a freelancer, you work independently or through platforms, completing specific annotation tasks assigned by companies or researchers. This work is essential because high-quality labeled data is required for AI systems to learn and make accurate predictions. Annotators may categorize images, transcribe speech, or highlight relevant information in documents. The flexibility of freelancing allows you to choose projects and work remotely.

What are some common challenges faced by freelance machine learning data annotators, and how can they be managed?

Freelance machine learning data annotators often encounter challenges such as maintaining data accuracy, handling repetitive tasks, and understanding complex annotation guidelines. Staying organized and regularly reviewing project instructions can help ensure consistency and quality in annotations. Additionally, communicating proactively with project managers and utilizing annotation tools efficiently can help manage workload and clarify uncertainties. Building expertise in different data types (text, image, audio) also allows annotators to diversify their projects and reduce monotony.
What are the most commonly searched types of Machine Learning Data Annotation jobs in Dallas, TX? The most popular types of Machine Learning Data Annotation jobs in Dallas, TX are:
What are popular job titles related to Freelance Machine Learning Data Annotation jobs in Dallas, TX? For Freelance Machine Learning Data Annotation jobs in Dallas, TX, the most frequently searched job titles are:
What job categories do people searching Freelance Machine Learning Data Annotation jobs in Dallas, TX look for? The top searched job categories for Freelance Machine Learning Data Annotation jobs in Dallas, TX are:
What cities near Dallas, TX are hiring for Freelance Machine Learning Data Annotation jobs? Cities near Dallas, TX with the most Freelance Machine Learning Data Annotation job openings:
Healthcare Statistical Data Scientist

Healthcare Statistical Data Scientist

SmartLight Analytics

Plano, TX • On-site, Remote

Full-time

Posted 22 hours ago


Job description

Overview
We're seeking a Machine Learning Data Scientist with deep expertise in healthcare claims data to design, build, and deploy advanced analytics and machine learning modeling solutions. In this role, you'll transform complex administrative and clinical datasets into actionable insights that improve cost efficiency, care quality, and operational performance across the healthcare ecosystem.
You'll collaborate with data engineers, clinicians, and product teams to develop predictive models, optimize workflows, and support strategic decision-making. This position is ideal for someone who thrives at the intersection of data science, healthcare operations, and modern machine learning.
Key Responsibilities
Machine Learning & Advanced Analytics
  • Develop, train, and deploy ML models for use cases such as:
  • Claims cost prediction and utilization forecasting
  • Fraud, waste, and abuse detection
  • Risk adjustment and member stratification
  • Provider performance and network optimization
  • Apply modern ML techniques including gradient boosting, deep learning, NLP, and probabilistic modeling.
  • Capable of applying advanced predictive analytics to correlate disparate datasets and events and derive business value.
  • Build scalable pipelines for feature engineering, model training, validation, and monitoring.

Healthcare Claims Expertise
  • Analyze and interpret medical, pharmacy, and dental claims (CPT/HCPCS, ICD-10, DRG, NDC).
  • Translate domain knowledge into meaningful features and model strategies.

Cross-Functional Collaboration
  • Partner with clinicians, product managers, and business stakeholders to define problems and measure outcomes.
  • Communicate complex analytical findings in clear, actionable terms.

Required Qualifications
  • Strong proficiency in Python and ML libraries (scikit-learn, XGBoost, TensorFlow/PyTorch).
  • Hands-on experience with healthcare claims datasets and coding systems.
  • Solid understanding of statistical modeling, machine learning algorithms, and data mining techniques.
  • Strong knowledge and expertise working with SQL.
  • Ability to translate business needs into analytical solutions.
  • Must have demonstrated the ability to solve complex problems with minimal direction.

Preferred Qualifications
  • Experience with NLP applied to clinical notes or unstructured healthcare data.
  • Familiarity with actuarial concepts, risk scoring, or value-based care models.
  • Familiarity deploying models into production (MLOps, CI/CD).
  • Background in health economics, epidemiology, or biostatistics.
  • Prior work with FHIR, HL7, or interoperability standards.

SmartLight Analytics was formed by a group of industry insiders who wanted to make a meaningful impact on the rising cost of healthcare. With this end in mind, SmartLight combats fraud, waste, and abuse in healthcare through our proprietary data analysis and model development. Requiring the bare minimum in employer involvement, our process works behind the scenes to save money without interrupting employee benefits or requiring employee behavior changes.