Data Science Intern (Python, SQL, Pandas)
Skillfied Mentor Jobs · India
- Hybrid
- Internship
- India
Job highlights
- Gain hands-on data science experience.
- Work with Python, SQL, and Pandas.
- Learn data cleaning and analysis.
- Build data models and visualizations.
- Receive placement support for top performers.
About the role
Data Science Intern (Python, SQL, Pandas)
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. Apply before 21st May to be considered for this opportunity.
Key skills/competency
- Data Science
- Python
- SQL
- Pandas
- Data Analysis
- Data Cleaning
- Data Preprocessing
- Exploratory Data Analysis
- Data Modeling
- Data Visualization
Skills & topics
- Data Science Intern
- Python
- SQL
- Pandas
- Data Analysis
- Data Cleaning
- Data Modeling
- Data Visualization
- Internship
- Remote
How to get hired
- Customize your resume: Highlight Python, SQL, Pandas, and data analysis skills.
- Highlight eagerness to learn: Emphasize your curious mindset and willingness to work on real projects.
- Apply promptly: Submit your application before the May 21st deadline.
- Showcase projects: If you have any personal projects, mention them to demonstrate practical skills.
Technical preparation
Practice Python coding challenges.,Work through SQL query exercises.,Build projects using Pandas.,Learn data visualization libraries.
Behavioral questions
Describe a challenging data problem.,How do you handle data errors?,Show your eagerness to learn.,How do you collaborate with a team?
Frequently asked questions
- What are the primary responsibilities of a Data Science Intern at Skillfied Mentor Jobs?
- As a Data Science Intern at Skillfied Mentor Jobs, you will work with data using Python, SQL, and Pandas, perform data cleaning and preprocessing, build basic data models, generate insights, and create reports and visualizations. You will also collaborate on real-world data projects.
- What are the eligibility criteria for the Data Science Intern role?
- Freshers and students are welcome. You need basic knowledge of Python, SQL, and Pandas, and an understanding of data analysis concepts. A curious mindset and willingness to learn are also essential.
- Is this Data Science Internship a paid position?
- This Data Science Internship is not stipend-based.
- What benefits can I expect as a Data Science Intern?
- You will gain hands-on experience with real datasets, receive an internship certificate, develop skills through project-based learning, and top performers will get 100% placement support.
- What is the application deadline for the Data Science Intern position?
- The application deadline is May 21st. It's recommended to apply early to be considered.
- What programming languages and tools are essential for this internship?
- Proficiency or basic knowledge in Python, SQL, and the Pandas library is essential for this Data Science Intern role.
- Can students apply for the Data Science Intern position?
- Yes, freshers and students are explicitly welcomed to apply for the Data Science Intern position.
- What kind of projects will I be working on as a Data Science Intern?
- You will collaborate with the team on real-world data projects, focusing on data cleaning, analysis, modeling, and visualization.