9 hours ago

Data Science Intern

ArGo Intern

Hybrid
Intern
$0
Hybrid

Job Overview

Job TitleData Science Intern
Job TypeIntern
Offered Salary$0
LocationHybrid

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Job Description

About the Data Science Intern Role at ArGo Intern

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

  • Data Analysis
  • Python
  • SQL
  • Pandas
  • Data Cleaning
  • Data Preprocessing
  • Exploratory Data Analysis (EDA)
  • Data Visualization
  • Data Modeling
  • Collaboration

Tags:

Data Science Intern
Data analysis
Data modeling
Visualization
Data cleaning
Preprocessing
EDA
Reporting
Collaboration
Insights
Project management
Python
SQL
Pandas
Jupyter
Matplotlib
Seaborn
Scikit-learn
Excel
Cloud platforms

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How to Get Hired at ArGo Intern

  • Research ArGo Intern's culture: Study their focus on skill development and intern support on platforms like LinkedIn.
  • Tailor your resume effectively: Highlight your Python, SQL, and Pandas skills, and any data analysis projects or coursework.
  • Showcase a curious mindset: Emphasize your eagerness to learn and problem-solve in your application and interviews.
  • Prepare for technical assessments: Practice fundamental SQL queries, Python data manipulation, and data analysis concepts.
  • Discuss relevant projects: Be ready to articulate your contributions and learnings from any data-related academic or personal projects.

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