1

Freelance Data Cleaning Jobs (NOW HIRING)

SC

$60.75 - $68.75/hr

Products must be clean, neat, and impeccably presented (spotless bottles, forward-facing labels ... The RAW format retains the maximum amount of image data captured by the camera sensor, allowing for ...

Own the creation of clean layouts, modern infographics, and establish a clear visual hierarchy to ... Transform raw data and concepts into professional, polished visual assets tailored to specific ...

About the Role This is a freelance role for a Tendem project. As a Senior Python Data Scraping ... Solid background in data cleaning, normalization, and validation, delivering structured datasets ...

Showing results 21-40

Freelance Data Cleaning information

See salary details

$14

$47

$132

How much do freelance data cleaning jobs pay per hour?

As of Aug 17, 2026, the average hourly pay for freelance data cleaning in the United States is $47.71, according to ZipRecruiter salary data. Most workers in this role earn between $24.28 and $61.78 per hour, depending on experience, location, and employer.

What is freelance data cleaning?

Freelance data cleaning involves working independently to organize, correct, and prepare data for analysis or use by businesses and organizations. Freelancers in this field identify and rectify errors, remove duplicates, fill in missing values, and format data sets to ensure accuracy and usability. This work can be project-based or ongoing, and often requires proficiency with tools like Excel, Python, or specialized data cleaning software. Clients may hire freelance data cleaners to improve decision-making, streamline processes, or prepare data for reporting and analytics.

What are the key skills and qualifications needed to thrive as a freelance data cleaning specialist?

To thrive as a Freelance Data Cleaning specialist, you need strong analytical skills, attention to detail, and a solid understanding of data management principles, commonly supported by experience with spreadsheets or a degree in a quantitative field. Familiarity with tools like Microsoft Excel, SQL, Python (especially pandas), and data visualization software is typically required. Strong communication, time management, and problem-solving skills help you collaborate with clients and deliver high-quality results efficiently. These skills ensure that data is accurate, reliable, and actionable, which is essential for informed business decision-making.

What are some common challenges freelance data cleaning professionals face when working with new clients' datasets?

Freelance data cleaning professionals often encounter challenges such as incomplete or inconsistent data formats, lack of clear documentation, and varying data quality standards across clients. Adapting quickly to different data management systems and understanding clients' specific data requirements are crucial for success in this role. Open communication with clients to clarify expectations and thorough initial data assessments can help mitigate many of these challenges and ensure a smoother workflow.

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

AspectFreelance Data CleaningData Analyst
CredentialsBasic Excel, data cleaning tools, sometimes certificationsDegree in data science, statistics, or related field; often certifications
Work EnvironmentRemote, project-based, flexible hoursOffice or remote, regular hours, team collaboration
Employer & IndustryClients across various industries, freelance platformsCompanies, organizations, corporate settings
Search & Comparison IntentFocus on cleaning and preparing dataAnalyzing data to generate insights

Freelance Data Cleaning involves independently preparing and cleaning data for clients, often on a project basis. Data Analysts typically perform broader data analysis, interpretation, and reporting within organizations. While both roles require data handling skills, Freelance Data Cleaning is more specialized in data preparation tasks, whereas Data Analysts focus on deriving insights from data sets.

More about Freelance Data Cleaning jobs

What cities are hiring for Freelance Data Cleaning jobs?

Cities with the most Freelance Data Cleaning job openings:

What are the most commonly searched types of Data Cleaning jobs?

The most popular types of Data Cleaning jobs are:

What states have the most Freelance Data Cleaning jobs?

States with the most job openings for Freelance Data Cleaning jobs include:

Infographic showing various Freelance Data Cleaning job openings in the United States as of August 2026, with employment types broken down into 50% Full Time, 20% Part Time, and 30% Contract. Highlights an 65% In-person, and 35% Remote job distribution, with an average salary of $99,230 per year, or $47.7 per hour.

Senior Python Data Scraping Engineer (Freelance)

Mindrift

New York, NY โ€ข On-site, Remote

$45/hr

Part-time

Re-posted 21 days ago


Job description

Mindrift is looking for highly skilled Vibecode 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 Senior 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 Senior 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 requirement.
  • 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 5+ 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 development tools and technologies, 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
  • Demonstrated experience handling anti-bot mechanisms and dynamic site structures at scale
  • Experience with cloud infrastructure (AWS or equivalent) and containerization (Docker) as part of real workflows
  • Hands-on experience with LLM frameworks (LangChain, OpenRouter, or similar) applied to automation tasks
  • 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 $45 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.