Data Analytics - Internship (WFH)

About the internship:Selected intern's day-to-day responsibilities include:

1. Collect, clean, organize, and validate datasets from different sources such as CSV files, spreadsheets, and databases.

2. Use SQL to retrieve, filter, join, and analyze data to answer business-related questions.

3. Perform exploratory data analysis using Python, Pandas, NumPy, and visualization libraries.

4. Create meaningful charts, reports, and interactive dashboards using tools such as Excel and Power BI.

5. Identify trends, patterns, anomalies, and key insights from datasets.

6. Work on real-world, project-based data analytics assignments under mentor guidance.

7. Translate analytical findings into clear business insights and actionable recommendations.

8. Maintain project documentation and use Git/GitHub for managing analytical projects and code.

9. Present project findings, dashboards, and recommendations during periodic review sessions.

10. Collaborate with mentors and team members to understand business problems and determine what the data can reveal.Who can apply:Only those candidates can apply who:are available for the work from home job/internshipcan start the work from home job/internship between 6th Oct'26 and 10th Nov'26are available for duration of 3 monthshave relevant skills and interestsStipend:INR₹ 5,000 - 8,000 /monthDeadline:[hidden]:59:59Other perks:Certificate, Letter of recommendation, Flexible work hours, 5 days a weekSkills required:Python, SQL, Git, MS-Excel, Problem Solving, Statistics, Business Analysis, Advanced Excel, Power BI, Tableau and PandasOther Requirements:1- Candidates should have a basic understanding of data analysis and genuine interest in working with data.2- Basic knowledge of SQL, Excel, or Python is preferred.3- Candidates should have good analytical and problem-solving skills.4- Strong attention to detail and willingness to learn are highly valued.5- Candidates should be comfortable working with datasets and identifying patterns or inconsistencies.6- Candidates should be willing to learn new tools such as Power BI and Python-based data analysis during the internship.7- Candidates with academic, personal, or hackathon-based data projects will be preferred.8- Candidates with a GitHub profile, portfolio, dashboards, or data-analysis projects are encouraged to share them.9- Candidates should be comfortable working independently and taking feedback during project reviews.10- Candidates must have access to a laptop and a stable internet connection.11- Consistency, learning attitude, and problem-solving ability will be valued more than prior professional experience.About Company:NextGen Forge Technologies is a technology studio specializing in web and app development, AI-driven solutions, and cloud/DevOps infrastructure. We help businesses turn ambitious ideas into practical, well-engineered products, building clean, fast websites and applications, integrating AI where it genuinely adds value, and setting up scalable cloud infrastructure that grows with the business.

We believe there is no one-size-fits-all approach to technology. Every engagement is shaped around the client's actual goals, constraints, and growth stage, not a generic template. Our core focus areas: web and app development, AI and machine learning, cloud and DevOps, and IT consulting. If you're a business looking for a technology partner who treats your project with the same care as their own, or a candidate looking to learn by actually building, we would like to hear from you.

Responsibilities

Selected intern's day-to-day responsibilities include:

1. Collect, clean, organize, and validate datasets from different sources such as CSV files, spreadsheets, and databases.

2. Use SQL to retrieve, filter, join, and analyze data to answer business-related questions.

3. Perform exploratory data analysis using Python, Pandas, NumPy, and visualization libraries.

4. Create meaningful charts, reports, and interactive dashboards using tools such as Excel and Power BI.

5. Identify trends, patterns, anomalies, and key insights from datasets.

6. Work on real-world, project-based data analytics assignments under mentor guidance.

7. Translate analytical findings into clear business insights and actionable recommendations.

8. Maintain project documentation and use Git/GitHub for managing analytical projects and code.

9. Present project findings, dashboards, and recommendations during periodic review sessions.

10. Collaborate with mentors and team members to understand business problems and determine what the data can reveal.