Data Science Intern
@ Webs IT Solution

Hybrid
₹15,000
Hybrid
Intern
Posted 16 hours ago

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XXXXXXXXXX XXXXXXXXXXX XXXXXXX******* @websitsolution.com
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Job Details

About Webs IT Solution

Webs IT Solution provides practical training and internship programs that help students and professionals gain expertise in AI, ML, and data-driven technologies.

Role Overview

As a Data Science Intern, you’ll work on end-to-end projects involving data preprocessing, machine learning model development, and predictive analytics.

Key Responsibilities

  • Perform data cleaning, feature engineering, and exploratory data analysis.
  • Build and evaluate machine learning models using Scikit-learn.
  • Visualize data insights using Matplotlib, Seaborn, or Power BI.
  • Work on real datasets to generate predictive solutions.
  • Collaborate with mentors to refine model performance.

Requirements

  • Knowledge of Python, Pandas, NumPy, Scikit-learn, and Matplotlib.
  • Understanding of ML algorithms, data preprocessing, and evaluation metrics.
  • Familiarity with SQL and Jupyter Notebooks.
  • Strong analytical thinking and curiosity for data-driven problem-solving.

Perks & Benefits

  • Certificate of Internship from Webs IT Solution.
  • Hands-on experience in ML and AI projects.
  • Mentorship from data scientists.
  • Networking and placement opportunities.

Stipend

₹7,500 – ₹15,000 (Performance-Based)

Key Skills/Competency

  • Python
  • Pandas
  • NumPy
  • Scikit-learn
  • Matplotlib
  • Machine Learning
  • Data Cleaning
  • Feature Engineering
  • Predictive Analytics
  • Data Visualization

How to Get Hired at Webs IT Solution

🎯 Tips for Getting Hired

  • Research Webs IT Solution's culture: Study their mission, values, and testimonials online.
  • Customize your resume: Highlight Python and ML project experience.
  • Prepare for technical questions: Review data preprocessing and algorithm fundamentals.
  • Practice interview insights: Be ready to discuss real data projects.

📝 Interview Preparation Advice

Technical Preparation

Practice Python coding challenges.
Review Pandas and NumPy data manipulation.
Study core ML algorithm concepts.
Experiment with Jupyter Notebook projects.

Behavioral Questions

Describe a team project experience.
Explain your problem-solving steps.
Discuss handling tight deadlines.
Share a learning moment from feedback.

Frequently Asked Questions