Data Cleaner Intern

4 weeks ago

India Zetheta Algorithms Private Limited Full time

About the Company

ZeTheta Algorithms Private Limited is a FinTech start-up which has been recently set up and is developing innovative AI tools.

About the Role We are seeking a detail-oriented and methodical student for Data Cleaning internship. This is an extraordinary opportunity for a self-driven, analytical student eager to learn about data processing, validation, and preparation for AI and machine learning applications.

Responsibilities

  • Assist in identifying and correcting errors, inconsistencies, and duplicates in large datasets.
  • Support data validation and quality assurance processes.
  • Help organize and standardize data formats across different sources.
  • Learn to use data cleaning tools and software like Excel, Google Sheets, and basic programming tools.
  • Assist in data entry and verification tasks to ensure accuracy.
  • Support the team in preparing clean datasets for analysis and AI model training.
  • Help document data cleaning processes and maintain data quality standards.

Qualifications

  • Currently enrolled in any undergraduate or graduate program.
  • Strong attention to detail and analytical mindset.
  • Basic proficiency with Excel or Google Sheets.
  • Good organizational skills and ability to work with large amounts of data.
  • Eagerness to learn about data processing and quality management.
  • Ability to work independently in a remote setting.
  • Patience and persistence for repetitive but important tasks.

Benefits

  • Opportunity to build practical skills with data processing and cleaning techniques.
  • Enhance your professional portfolio with real-world data management experience.
  • Exposure to AI and FinTech data workflows in a remote work environment.
  • Mentorship and guidance from experienced data professionals.
  • Hands-on learning experience with data quality and validation processes.

Internship Details

  • Duration: Self Paced with options of 1, 2, 3, 4 or 6 months.
  • Type: Unpaid

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