Data Analyst Intern
@ UM IT Solutions

Hybrid
₹180,000
Hybrid
Intern
Posted 6 hours ago

Your Application Journey

Personalized Resume
Apply
Email Hiring Manager
Interview

Email Hiring Manager

XXXXXXXXXX XXXXXXXXXXX XXXXXXXXXX******* @webboostsolutionsbyum.com
Recommended after applying

Job Details

About Data Analyst Intern

WebBoost Solutions by UM offers students and graduates hands-on experience in data analysis. Gain real-world skills and enhance your career prospects during a 3-month internship.

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)
  • Real-world data analysis experience
  • Certificate of Internship & 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
  • data visualization
  • reporting
  • datasets
  • Excel
  • SQL
  • Python
  • trend analysis
  • communication
  • teamwork
Apply without a personalized resume

How to Get Hired at UM IT Solutions

🎯 Tips for Getting Hired

  • Customize your resume: Highlight data analysis projects and tools.
  • Research WebBoost: Understand their mission and culture.
  • Showcase technical skills: Emphasize Excel, SQL, and Python.
  • Prepare for interviews: Practice data cleaning and visualization questions.

📝 Interview Preparation Advice

Technical Preparation

Practice SQL queries.
Master Excel functions.
Review Python basics.
Analyze sample datasets.

Behavioral Questions

Describe teamwork experiences.
Explain handling analytical challenges.
Showcase detail orientation.
Discuss past collaboration instances.

Frequently Asked Questions