Want to get hired at UM IT PRIVATE LIMITED?

Data Analyst Intern

UM IT PRIVATE LIMITED

HybridHybrid

Original Job Summary

About the Data Analyst Intern Role

UM IT PRIVATE LIMITED, operating under the name WebBoost Solutions by UM, is offering a paid Data Analyst Intern opportunity. This role is remote and lasts for 3 months, with potential for a full-time role based on performance. Interns will receive an Internship Certificate and gain real-world experience in data analysis.

Responsibilities

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

Requirements

  • Enrollment in or graduation from a relevant program
  • Strong analytical skills and attention to detail
  • Familiarity with tools like Excel, SQL, or Python (preferred)
  • Excellent communication and teamwork abilities

Stipend & Benefits

  • Stipend: ₹7,500 - ₹15,000 (Performance-Based)
  • Real-world data analysis experience
  • Internship Certificate & Letter of Recommendation
  • 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
  • Teamwork
  • Communication
  • Attention to Detail

How to Get Hired at UM IT PRIVATE LIMITED

🎯 Tips for Getting Hired

  • Research UM IT PRIVATE LIMITED: Study company culture and recent projects.
  • Customize your resume: Highlight data analytics skills and project experiences.
  • Prepare case studies: Demonstrate your analytical problem-solving abilities.
  • Practice technical interviews: Focus on SQL, Excel, and Python problems.

📝 Interview Preparation Advice

Technical Preparation

Practice Excel data tasks.
Review SQL query syntax.
Brush up on Python basics.
Study data visualization techniques.

Behavioral Questions

Describe a team challenge.
Explain a project learning experience.
Detail handling data discrepancies.
Discuss time management in projects.