Data Science Intern
Company: Arowva Development
Job Type: Internship
Experience: Fresher / Entry Level
Duration: 1 Month / 2 Months / 3 Months
Stipend: Performance-Based ₹1,000 – ₹8,000 per month
Work Schedule: Flexible Working Hours
Work Mode: Remote / Hybrid / On-site
Job Description
Arowva Development is looking for a motivated and enthusiastic Data Science Intern who is interested in Python, data analysis, machine learning, and solving real-world problems using data.
This internship is suitable for students, freshers, and aspiring data professionals who want to gain practical experience and work on real-world projects under the guidance of mentors.
The selected candidate will work with datasets, perform data analysis, create visualizations, develop basic machine learning models, and contribute to assigned data-driven projects.
Key Responsibilities
- Collect, clean, preprocess, and analyze datasets.
- Perform exploratory data analysis (EDA).
- Identify patterns, trends, and insights from data.
- Work with Python and data science libraries.
- Build and evaluate basic machine learning models.
- Create data visualizations and reports.
- Prepare datasets for analysis and machine learning.
- Assist in developing data-driven solutions.
- Document analysis, experiments, and results.
- Collaborate with mentors and team members.
- Complete assigned tasks within project deadlines.
Required Skills
- Basic knowledge of Python.
- Basic understanding of Data Science.
- Knowledge of data analysis and visualization.
- Basic understanding of statistics and mathematics.
- Basic SQL knowledge.
- Good problem-solving skills.
- Willingness to learn and work on real-world projects.
Good to Have
- NumPy
- Pandas
- Matplotlib
- Seaborn
- Scikit-learn
- Jupyter Notebook / Google Colab
- Machine Learning fundamentals
- Power BI / Tableau
- Git and GitHub
Knowledge of AI, Deep Learning, NLP, or Generative AI will be an advantage but is not mandatory.
Internship Duration
The internship is available for:
- 1 Month
- 2 Months
- 3 Months
The final duration will be confirmed during the selection and onboarding process.
Stipend
₹1,000 – ₹8,000 per month
The stipend is performance-based and may vary depending on:
- Quality of work
- Task completion
- Technical skills
- Project contribution
- Learning progress
- Consistency
- Professional conduct
Working Hours
Flexible Working Hours
Interns can manage their working schedule flexibly while maintaining project deadlines, mentor meetings, team coordination, and assigned responsibilities.
What You Will Learn
- Python for Data Science
- Data Cleaning and Preprocessing
- Exploratory Data Analysis
- Data Visualization
- Statistical Analysis
- SQL
- Machine Learning Fundamentals
- Model Training and Evaluation
- Real-world Data Science Projects
- Git and GitHub
- Technical Documentation
- Professional Project Workflow
Who Can Apply?
- BCA students
- B.Sc. Computer Science / Data Science students
- B.Tech / B.E. students
- MCA students
- Recent graduates
- Freshers
- Students interested in Data Science and Machine Learning
Internship Benefits
- Practical Data Science experience
- Real-world project exposure
- Technical mentorship
- Flexible working hours
- Performance-based stipend
- Project-based learning
- Professional work experience
- Internship completion certificate, subject to successful completion
- Portfolio-building opportunities
Selection Process
1. Application Review
2. Shortlisting
3. Technical / Data Science Assessment
4. Interview / Discussion
5. Selection and Onboarding
Important Note
This is a learning and project-oriented internship. Interns are expected to actively participate, complete assigned tasks, communicate with mentors, and maintain professional conduct throughout the internship.
The stipend is performance-based and ranges from ₹1,000 to ₹8,000 per month. The actual stipend may vary based on individual performance and contribution.
Apply now to gain practical Data Science experience with Arowva Development.
Pay: ₹1,000.00 - ₹8,000.00 per month
Benefits:
- Flexible schedule
Work Location: Remote
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