Data Analyst Intern
@ UM IT Solutions

Hybrid
₹15,000
Hybrid
Intern
Posted 8 hours ago

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XXXXXXXX XXXXXXXXXXX XXXXXXXXXX***** @umitsolutions.com
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Job Details

About Data Analyst Intern

WebBoost Solutions by UM offers a paid internship for students and recent graduates to gain hands-on experience in data analysis. This remote opportunity lasts for 3 months with potential for a full-time role based on performance, along with an internship certificate.

Responsibilities

  • Collect, clean, and analyze datasets.
  • Develop reports and data visualizations.
  • Identify trends and patterns in data.
  • Collaborate on presentations and insights.

Requirements

  • Enrolled in or a graduate of a relevant program.
  • Strong analytical skills and attention to detail.
  • Familiarity with Excel, SQL, or Python (preferred).
  • Excellent communication and teamwork abilities.

Stipend & Benefits

  • Stipend: ₹7,500 - ₹15,000 (Performance-Based and Paid).
  • Real-world data analysis experience.
  • Certificate of Internship & Letter of Recommendation.
  • Opportunity to build your portfolio with impactful projects.

How to Apply

Submit your application with the subject line "Data Analyst Intern Application." WebBoost Solutions by UM welcomes applicants from all backgrounds.

Key skills/competency

  • Data Analysis
  • Excel
  • SQL
  • Python
  • Data Cleaning
  • Reporting
  • Visualization
  • Collaboration
  • Attention to Detail
  • Communication
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How to Get Hired at UM IT Solutions

🎯 Tips for Getting Hired

  • Research UM IT Solutions: Understand company background and values.
  • Customize your resume: Highlight data analysis projects.
  • Emphasize technical skills: Excel, SQL, Python expertise matter.
  • Prepare for interviews: Review common data analysis questions.

📝 Interview Preparation Advice

Technical Preparation

Refresh Excel formulas and functions.
Practice SQL queries and database operations.
Work on Python data analysis libraries.
Review data cleaning and visualization techniques.

Behavioral Questions

Describe a project managing data challenges.
Explain team collaboration on analysis tasks.
Discuss how you handle tight deadlines.
Share an instance of learning new tools.

Frequently Asked Questions