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Internship Data Cleaning Jobs (NOW HIRING)

Identify trends, patterns, and insights from datasets * Assist in data cleaning, validation, and ... internships in Business Intelligence, Data Analysis, or Reporting * Strong analytical and problem ...

This 12-week Internship Program (May 18-Aug 7, 2026) is a gateway to full-time career paths for ... which may include data cleaning, data mining, data clustering and data preparation for ...

This internship offers a unique blend of responsibilities, allowing you to develop a diverse skill ... Assisting in collecting, cleaning, and analyzing data from various sources * Developing and ...

Data Tools Associate

Atlanta, GA · On-site

$56K - $57K/yr

Document and data cleaning - Write and maintain internal and external documentation that promotes ... Knowledge of and 6 months of experience (Internships Count!), working with programming languages ...

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Internship Data Cleaning information

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How much do internship data cleaning jobs pay per hour?

As of Jul 7, 2026, the average hourly pay for internship data cleaning in the United States is $22.50, according to ZipRecruiter salary data. Most workers in this role earn between $17.31 and $24.52 per hour, depending on experience, location, and employer.

What typical challenges might I encounter during a Data Cleaning internship, and how can I effectively address them?

During a Data Cleaning internship, you may encounter challenges such as dealing with large volumes of inconsistent or incomplete data, identifying and correcting errors, and understanding the context behind various data sets. Effective strategies include developing a solid grasp of data validation techniques, becoming proficient with tools like Excel, Python, or SQL, and regularly communicating with team members to clarify data ambiguities. Being proactive in asking questions and seeking feedback will help you grow your technical skills and contribute more efficiently to the team’s data quality goals.

What is an Internship Data Cleaning position?

An Internship Data Cleaning position involves assisting organizations in organizing, cleaning, and preparing their data for analysis. Interns in this role typically use software tools or programming languages to identify and correct errors, remove duplicates, and standardize formats within datasets. This foundational work ensures that data is accurate and reliable for further analysis or reporting. Such internships are a great way for students or recent graduates to gain practical experience in data management and analytics.

What is the difference between Internship Data Cleaning vs Data Analyst Intern?

AspectInternship Data CleaningData Analyst Intern
Required SkillsBasic data cleaning, Excel, SQLData cleaning, analysis, visualization
Work EnvironmentEntry-level, supervised tasksProject-based, collaborative
Industry UsageCommon in tech, finance, healthcareBroader, includes reporting and insights
CertificationsNone typically requiredOptional certifications in data analysis

Internship Data Cleaning focuses on basic data preparation tasks, while Data Analyst Interns handle more comprehensive analysis and reporting. Both roles are entry-level and often found in similar industries, but Data Analyst Interns typically require broader skills and responsibilities.

What are the key skills and qualifications needed to thrive as an Internship Data Cleaning professional, and why are they important?

To thrive as an Internship Data Cleaning professional, you need a basic understanding of data management, attention to detail, and familiarity with database concepts, often supported by coursework in data analysis or statistics. Proficiency with tools like Microsoft Excel, Google Sheets, and basic knowledge of SQL or Python for data manipulation is typically required. Strong organizational skills, problem-solving ability, and effective communication help interns stand out in this role. These competencies are crucial to ensure data accuracy, support analytical tasks, and maintain data quality for business or research needs.
More about Internship Data Cleaning jobs
What cities are hiring for Internship Data Cleaning jobs? Cities with the most Internship 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 Internship Data Cleaning jobs? States with the most job openings for Internship Data Cleaning jobs include:
Infographic showing various Internship Data Cleaning job openings in the United States as of July 2026, with employment types broken down into 61% Full Time, 38% Part Time, and 1% Temporary. Highlights an 100% Physical job distribution, with an average salary of $46,809 per year, or $22.5 per hour.
Internship - Data Management

Internship - Data Management

QuEra Computing, Inc.

Boston, MA • On-site

Internship

Re-posted 4 days ago


Job description

About QuEra Computing, Inc.
QuEra Computing is building the world's most powerful neutral-atom quantum computers. Our systems are designed to scale and enable groundbreaking advances in science and technology. We collaborate closely with leading academic and industry partners to push the boundaries of quantum computing, error correction, and fault tolerance.
Summary
The Photonics team at QuEra pioneers cutting-edge photonic chips for integration into neutral-atom quantum computers. QuEra Computing Inc. seeks a Photonics Data Engineer Intern to develop an AI-powered data infrastructure that supports our design, fabrication, and testing workflows. You'll develop tools that transform raw measurement and metrology data into actionable insights, directly informing how we design better photonic chips faster for large-scale neutral atom quantum computers.
Responsibilities
  • AI-powered Data Infrastructure: Develop an AI-powered data management infrastructure for photonic integrated circuit (PIC) design, fabrication, and testing workflows.
  • Automation and Tooling: Write Python functions and utilities to automate data ingestion, cleaning, and organization across multiple data sources.
  • Performance Analysis Pipelines: Build analysis pipelines to extract key device performance metrics (e.g., insertion loss, extinction ratio, bandwidth, yield). Analyze fabrication metrology datasets from multiple foundries and correlate findings with device performance to identify process-performance relationships.
  • Cross-functional Collaboration: Work with other photonics engineers to define data schemas and best practices for reproducible design and testing workflows.
  • Documentation: Document data infrastructure and analysis workflows for long-term team use.

Qualifications
  • Currently pursuing or recently completed a Bachelor's or Master's degree in Computer Science, Physics, Mathematics, or a related discipline.
  • Strong proficiency in Python programming, with hands-on experience using AI and data science libraries including PyTorch, NumPy, SciPy, and Pandas, and familiarity with workflow automation tools.
  • Working knowledge of data storage formats, database design principles, and data analysis and visualization frameworks.
  • Proven track record of leveraging Python and AI tools to tackle challenging problems in science and physics.
  • Strong analytical mindset with exceptional problem-solving capabilities.
  • Excellent interpersonal and communication skills, with the ability to collaborate effectively across multidisciplinary teams.
  • Clear evidence of self-motivation and the ability to drive independent projects to completion.
  • While a deep background in quantum physics is not a prerequisite, a solid understanding of computer science and mathematics in the context of physical simulation and experimental analysis is required.

On-site internship. There is no relocation offered for this role.
QuEra is committed to cultivating a diverse work environment and is proud to be an equal opportunity employer. We highly value diversity in our current and future employees and do not discriminate (including in our hiring and promotion practices) based on race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status, or any other characteristic protected by law.