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Part Time Data Cleaning Jobs (NOW HIRING)

Chicago Public Schools

Senior Data Analyst

Chicago, IL · On-site

$88K - $111K/yr

This position will be held accountable for the following responsibilities: • Collect, clean, and ... The Chicago residency requirement does not apply to temporary/part-time positions, however, all CPS ...

Booz Allen Hamilton, Inc.

Data Engineer

Beavercreek, OH · On-site

$99K - $225K/yr

You Have: * 5+ years of experience with data exploration, data cleaning, data analysis, data ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...

Booz Allen Hamilton, Inc.

Data Engineer

Beavercreek, OH · On-site

$99K - $225K/yr

You Have: * 5+ years of experience with data exploration, data cleaning, data analysis, data ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...

Booz Allen Hamilton, Inc.

Data Scientist, Mid

Reston, VA · On-site

$77K - $176K/yr

You Have: * 3+ years of experience with data exploration, data cleaning, data visualization, or ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...

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Part Time Data Cleaning information

What are the key skills and qualifications needed to thrive as a Part Time Data Cleaning professional, and why are they important?

To thrive as a Part Time Data Cleaning professional, you need strong attention to detail, basic data analysis skills, and familiarity with spreadsheet software, often supported by a high school diploma or equivalent. Proficiency with tools like Microsoft Excel, Google Sheets, and sometimes data cleaning platforms such as OpenRefine is typically required. Strong organizational skills, problem-solving abilities, and reliability help individuals excel in this role. These skills ensure that data is accurate, consistent, and ready for analysis, directly impacting the quality of business decisions.

What is the difference between Part Time Data Cleaning vs Part Time Data Entry?

AspectPart Time Data CleaningPart Time Data Entry
Required SkillsAttention to detail, basic data management, familiarity with cleaning toolsTyping speed, accuracy, basic computer skills
Work EnvironmentRemote or office, often involves reviewing and cleaning datasetsRemote or office, involves inputting data into systems
Common CertificationsNone typically required, but familiarity with Excel or data tools helpsNone typically required, basic computer proficiency needed

Part Time Data Cleaning focuses on reviewing and correcting datasets to ensure accuracy, while Part Time Data Entry involves inputting data into systems. Both roles often require basic computer skills and can be performed remotely or in an office setting. Data Cleaning emphasizes accuracy and attention to detail, whereas Data Entry emphasizes speed and typing skills.

What are some common challenges faced by part-time data cleaning professionals, and how can they be effectively managed?

Part-time data cleaning professionals often encounter challenges such as handling large volumes of inconsistent or incomplete data, working within tight deadlines, and understanding the context of unfamiliar datasets. To manage these challenges, it's important to develop strong attention to detail, communicate regularly with data owners or team members for clarifications, and utilize data cleaning tools or scripts to improve efficiency. Establishing a routine for documenting changes and maintaining clear records can also help ensure data quality and consistency, even when working limited hours.

What is part time data cleaning?

Part time data cleaning involves working on a flexible or reduced schedule to organize, correct, and prepare data for analysis. The main responsibilities include identifying and removing duplicate or inaccurate records, standardizing formats, and ensuring data completeness and reliability. This role is important for businesses and organizations that rely on accurate data for decision-making, but do not require a full-time data specialist. Part time data cleaners may use tools like Excel, Google Sheets, or specialized data cleaning software. The position can be remote or onsite, depending on the employer's needs.
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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 Part Time Data Cleaning jobs? States with the most job openings for Part Time Data Cleaning jobs include:
What job categories do people searching Part Time Data Cleaning jobs look for? The top searched job categories for Part Time Data Cleaning jobs are:
Part Time Data Cleaning jobs near you
Infographic showing various Part Time Data Cleaning job openings in the United States as of May 2026, with employment types broken down into 100% Part Time. Highlights an 85% In-person, and 15% Remote job distribution.

Freelance Data Scraping Engineer (Python)

Mindrift

Dallas, TX • Remote

$37/hr

Part-time

Posted 23 days ago

Job description

Mindrift is looking for highly skilled Python Data Scraping Engineers to join the Tendem project and drive specialized data scraping workflows within our hybrid AI + human system.

In this role, as an AI Pilot - that's how we refer to this role at Mindrift - you'll collaborate with Tendem Agents that handle repetitive tasks, while you provide critical thinking, domain expertise, and quality control to deliver accurate and actionable 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 AI projects from major tech innovators. Our mission is to unlock the potential of Generative AI by tapping into real-world expertise from across the globe.

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 various tools such as our provided Apify and OpenRouter alongside your own resourceful approaches.

Key Responsibilities

  • Own end-to-end data extraction workflows across complex websites, ensuring complete coverage, accuracy, and reliable delivery of structured datasets.
  • Leverage internal tools (Apify, OpenRouter) alongside 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.

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.

How to get started

Simply apply to this post, qualify, and get the chance to contribute to projects that match your technical skills, on your own schedule. From coding and automation to fine-tuning AI outputs, you'll play a key role in advancing AI capabilities and real-world applications.

Requirements

  • At least 3 year 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.
  • 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).
  • 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).

Benefits

Why this freelance opportunity might be a great fit for you?

  • Work fully remote on your own schedule with just a laptop and stable internet connection.
  • Gain hands-on experience in a unique hybrid environment where human expertise and AI agents collaborate seamlessly - a distinctive skill set in a rapidly growing field.
  • Participate in performance-based bonus programs that reward high-quality work and consistent delivery.

Apply