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Freelance Data Science Jobs in Texas (NOW HIRING)

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Freelance Data Science information

See Texas salary details

$34.9K

$114.3K

$183.1K

How much do freelance data science jobs pay per year?

As of Aug 1, 2026, the average yearly pay for freelance data science in Texas is $114,350.00, according to ZipRecruiter salary data. Most workers in this role earn between $91,800.00 and $126,700.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Freelance Data Scientist, and why are they important?

To thrive as a Freelance Data Scientist, you need strong proficiency in statistics, programming (commonly Python or R), and data analysis, often backed by a degree in a quantitative field or relevant certifications. Mastery of tools like Jupyter Notebook, SQL, machine learning libraries (e.g., scikit-learn, TensorFlow), and experience with cloud platforms are typically required. Excellent communication, self-motivation, and time management skills set successful freelancers apart by enabling effective client collaboration and project delivery. These abilities ensure you can independently deliver actionable insights and solutions that meet diverse client needs in a competitive market.

What are freelance data scientists?

Freelance data scientists are independent professionals who analyze, interpret, and extract insights from data for clients on a project or contract basis, rather than working as full-time employees for a single organization. They leverage skills in statistics, programming, and machine learning to solve business problems, build predictive models, and visualize data. Freelance data scientists often work with multiple clients across various industries, providing flexibility and the ability to specialize in different types of data projects. Their work may include tasks such as data cleaning, exploratory data analysis, algorithm development, and reporting findings to stakeholders.

Can data scientists make $300k?

Data scientists can earn $300,000 or more annually, especially with extensive experience, advanced skills in machine learning, and work in high-paying industries or senior roles. Achieving this level often requires a strong portfolio, specialized certifications, and sometimes working in competitive markets or consulting environments.

What is the 80 20 rule in data science?

In data science, the 80/20 rule, also known as Pareto principle, suggests that roughly 80% of results come from 20% of the efforts or features. Data scientists often use this concept to focus on the most impactful variables or tasks to improve model performance efficiently.

Is 40 too late for data science?

Age is not a barrier to becoming a freelance data scientist. Success depends on skills, experience, and continuous learning of tools like Python, R, and machine learning techniques, regardless of age. Many professionals transition into data science later in their careers and find opportunities in the field.

What is the difference between Freelance Data Science vs Data Analyst?

AspectFreelance Data ScienceData Analyst
CredentialsTypically requires a degree in data science, statistics, or related fields; certifications like CAP or Microsoft Data AnalystOften requires a degree in statistics, mathematics, or related fields; certifications like Microsoft Data Analyst or Tableau
Work EnvironmentIndependent, project-based, remote or on-siteUsually employed within organizations, working in teams or departments
Employer & Industry UsageFreelance data science projects across various industries like tech, finance, healthcareIn-house roles in industries such as finance, marketing, healthcare, and retail

Freelance Data Science involves independent, project-based work requiring advanced skills in machine learning, programming, and statistical analysis. Data Analysts typically focus on interpreting existing data, creating reports, and visualizations within organizations. While both roles require strong analytical skills, freelance data scientists often handle more complex modeling tasks, whereas data analysts focus on data interpretation and reporting.

What are the most common challenges faced by freelance data scientists when working with clients remotely?

Freelance data scientists often encounter challenges such as unclear project scopes, varying data quality, and communication gaps when collaborating remotely with clients. It's essential to establish clear expectations, maintain regular updates, and set milestones to ensure both parties are aligned throughout the project. Additionally, freelancers may need to adapt to different tools or platforms based on each client's preferences, requiring flexibility and strong self-management skills. Building trust and delivering insights in a clear, actionable manner can help foster long-term client relationships.

Can I be a freelance data scientist?

Yes, a data scientist can work as a freelancer by offering services such as data analysis, modeling, and machine learning to clients independently. Successful freelancing typically requires strong technical skills, proficiency with tools like Python or R, and the ability to manage projects and communicate findings effectively.
What are the most commonly searched types of Data Science jobs in Texas? The most popular types of Data Science jobs in Texas are:
What job categories do people searching Freelance Data Science jobs in Texas look for? The top searched job categories for Freelance Data Science jobs in Texas are:
What cities in Texas are hiring for Freelance Data Science jobs? Cities in Texas with the most Freelance Data Science job openings:
Infographic showing various Freelance Data Science job openings in Texas as of July 2026, with employment types broken down into 1% As Needed, 84% Full Time, 11% Part Time, 1% Temporary, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $114,350 per year, or $55 per hour.

Freelance Data Scraping Engineer (Python)

Mindrift

Dallas, TX • Remote

$37/hr

Part-time

Re-posted 19 days ago


Job description

Mindrift is looking for highly skilled Web Scraping specialists to join the Tendem project (https://tendem.ai/) and drive specialized data scraping workflows for real-world use cases.

Mindrift is looking for highly skilled Python Data Scraping Engineers to join the Tendem project and drive specialized data scraping workflows for real-world applications.

In this role, you'll apply your expertise in web scraping, data extraction, and data processing to deliver accurate, reliable, and high-quality results. This part-time remote opportunity is ideal for technical professionals with hands-on experience in web scraping, data extraction, and processing.

What We Do 

The Mindrift platform connects specialists with innovative technology projects. Our mission is to help develop high-quality AI technologies by combining real-world expertise from professionals across the globe with advanced AI development efforts.

About the Role

This is a freelance role for a Tendem project. As a Python Data Scraping Engineer, you'll handle data scraping tasks requiring technical precision for web extraction and processing, utilizing tools such as Apify, OpenRouter, and other technologies, alongside your own technical expertise and approaches. 

Key Responsibilities

  • Own end-to-end data extraction workflows across complex websites, ensuring complete coverage, accuracy, and reliable delivery of structured datasets.
  • Leverage available tools and custom workflows to accelerate data collection, validation, and task execution while meeting defined requirements.
  • Ensure reliable extraction from dynamic and interactive web sources, adapting approaches as needed to handle JavaScript-rendered content and changing site behavior.
  • Enforce data quality standards through validation checks, cross-source consistency controls, adherence to formatting specifications, and systematic verification prior to delivery.
  • Scale scraping operations for large datasets using efficient batching or parallelization, monitor failures, and maintain stability against minor site structure changes.

Educational qualifications

  • At least 3+ years of relevant experience in data engineering, web scraping, automation, or software development (required).
  • Bachelor's or Master's Degree in Engineering, Applied Mathematics, Computer Science, or related technical fields is a plus.

Academic and/or Professional Experience

Candidates should have a strong technical foundation and practical experience with scripting, automation, and data extraction workflows. We are looking for specialists who can solve non-trivial problems, work confidently with modern web technologies and data processing tools, and systematically collect, structure, and validate data from diverse sources. A methodical, detail-oriented approach and the ability to work independently are essential.

Technical Skills (Essential)

  • Strong experience in Python web scraping (BeautifulSoup, Selenium or similar), including dynamic content (JS, AJAX, infinite scroll) and APIs via proxies
  • Proven ability to extract data from complex structures (hierarchies, archived pages, inconsistent HTML)
  • Solid background in data cleaning, normalization, and validation, delivering structured datasets (CSV, JSON, Google Sheets)

Additional requirements

  • Hands-on experience with LLMs and AI frameworks to enhance automation and problem-solving
  • Strong attention to detail and commitment to data accuracy
  • Self-directed work ethic with ability to troubleshoot independently
  • A link to GitHub is a plus
  • English proficiency: Upper-intermediate (B2) or above (required)

Project time expectations 

For this project, tasks are estimated to require around 10-20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active.

Compensation 

On this project, contributors can earn up to $37 per hour equivalent, depending on their level and pace of contribution.

Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.