9 days ago

Data Science Intern

Wake Up Whistle

Hybrid
Intern
$0
Hybrid

Job Overview

Job TitleData Science Intern
Job TypeIntern
CategoryCommerce
Experience5 Years
DegreeMaster
Offered Salary$0
LocationHybrid

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Job Description

Data Science Intern at Wake Up Whistle

We are seeking passionate and driven Data Science Interns who are eager to learn, work with real datasets, and build a strong foundation in data science.

Roles & Responsibilities

  • Work with data using Python, SQL, and Pandas
  • Perform data cleaning, preprocessing, and exploratory data analysis (EDA)
  • Build basic data models and generate insights
  • Create reports and visualizations to support business decisions
  • Collaborate with the team on real-world data projects

Eligibility Criteria

  • Freshers and students are welcome
  • Basic knowledge of Python, SQL, and Pandas
  • Understanding of data analysis concepts
  • Curious mindset and willingness to learn

Internship Details

  • Mode: Virtual / Remote
  • Duration: Flexible
  • Stipend: Not stipend based

Perks & Benefits

  • Hands-on experience with real datasets
  • Internship Certificate
  • Skill development & project-based learning
  • Top performers will receive 100% placement support

How to Apply

Interested candidates can apply by clicking on the “Apply” option.

Key skills/competency

  • Python
  • SQL
  • Pandas
  • Data Cleaning
  • Data Preprocessing
  • Exploratory Data Analysis (EDA)
  • Data Modeling
  • Data Visualization
  • Business Intelligence
  • Data Analysis Concepts

Tags:

Data Science Intern
Data Cleaning
Data Preprocessing
Exploratory Data Analysis
Data Modeling
Reporting
Visualization
Business Decisions
Project Collaboration
Insight Generation
Learning
Python
SQL
Pandas
Jupyter
NumPy
SciPy
Matplotlib
Seaborn
Excel
Tableau

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How to Get Hired at Wake Up Whistle

  • Research Wake Up Whistle's mission: Study their goals, values, and how data science contributes to their success.
  • Tailor your resume: Highlight your Python, SQL, and Pandas skills, showcasing any relevant projects or coursework.
  • Showcase your data portfolio: Present academic or personal data analysis and visualization projects.
  • Prepare for technical questions: Review data manipulation, SQL queries, and basic EDA concepts thoroughly.
  • Emphasize your learning aptitude: Demonstrate a curious mindset and strong willingness to learn and adapt to new challenges.

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