SKIDEV Edutech Private Limited has advertised a six-month, work-from-home Data Analytics internship on Internshala. The listing combines Python, SQL, Excel and dashboard work, making it relevant to applicants who want practical exposure to analysing information and explaining business findings. There are seven advertised openings, and the application deadline is 21 October 2026. The employer asks applicants to be available for the full internship and to start within the window stated on the listing.
The compensation needs careful reading. The headline range includes incentives: the fixed stipend is ₹10,000–15,000 per month, with an additional ₹3,000–5,000 in monthly incentives advertised separately. The upper combined figure is not a guaranteed fixed stipend. This article is based on the employer's live Internshala listing checked on 25 September 2026; Jobsii is sharing the opportunity, not recruiting on SKIDEV's behalf.
Internship details at a glance
- Role: Data Analytics intern.
- Employer: SKIDEV Edutech Private Limited.
- Work arrangement: work from home, full-time internship.
- Duration: six months.
- Openings advertised: seven.
- Fixed monthly stipend: ₹10,000–15,000.
- Additional advertised incentives: ₹3,000–5,000 per month, subject to the employer's terms.
- Start window: 21 September to 26 October 2026.
- Apply by: 21 October 2026.
- Listed benefits: certificate, recommendation letter and a five-day working week.
What the work involves
The responsibilities cover several stages of an analytics assignment. Interns will collect and analyse information from different sources, use analytical models or algorithms to support business processes, and prepare dashboards that make results easier to understand. The employer specifically mentions Power BI and Tableau alongside Python and SQL. Applicants should therefore expect a combination of data handling, visual reporting and communication rather than a role focused only on writing code.
Reports and presentations for management are part of the advertised scope. The listing also refers to working with other teams, supporting data-informed decisions, handling additional analytical requests and troubleshooting. Those points matter because an analyst's output must answer a useful question. Producing a chart is only one step; checking what the numbers represent and explaining their limitations are equally important to reliable work.
The employer describes SKIDEV as an education-technology business working in data and business-domain upskilling. That description provides context, but the listing does not identify the exact datasets, client assignments or internal systems an intern will access. It also does not promise a particular machine-learning project. Applicants should ask about the actual workstream during selection instead of assuming every listed tool will be used every day.
Eligibility and skills to check
The listing asks for relevant skills and interests, full-time work-from-home availability and a six-month commitment. It does not specify a mandatory degree, graduation batch, minimum CGPA or a fixed number of years of experience in the eligibility information reviewed. That absence should not be converted into a claim that everyone is guaranteed to qualify. Selection remains with the employer, which can assess whether an applicant has the required foundations.
The skills named are Python, SQL, data analytics, MS Excel, data science, Power BI and Tableau. For a student, a well-explained academic or personal project can demonstrate those foundations more clearly than a long list of course certificates. For someone changing domains, the useful question is whether they can show careful analysis, reproducible steps and clear communication, not merely familiarity with software names.
Before applying, check the six-month commitment against classes, examinations and any existing employment. Work from home describes location, not an unrestricted timetable. The listing advertises five working days, but it does not publish daily hours, equipment provision or an internet reimbursement policy. These should be clarified with the employer before accepting an offer.
Understanding the stipend correctly
Use the fixed component when making a personal budget. The advertised fixed range is ₹10,000–15,000 each month; the incentive range is separate. The listing does not explain the performance formula, eligibility conditions, payment cycle or how a candidate's fixed amount is chosen within the range. Obtain those details in the written offer. Do not assume that every intern receives the top fixed amount or the full incentive.
The certificate and recommendation letter are listed benefits, not a promise of permanent employment. No guaranteed conversion to a full-time job is stated in the information reviewed. Likewise, the six-month duration should not be presented as a paid training course that applicants must purchase. If anyone requests a course fee or payment to secure this internship, check the request through the actual listing and platform before proceeding.
How to apply
- Open the SKIDEV Data Analytics internship listing on Internshala.
- Confirm that the employer, role, duration and stipend split still match the current advertisement and that applications remain open.
- Sign in to your own Internshala account and update your education, skills, availability and project information.
- Use the listing's application process and answer the employer's questions accurately. Explain your actual contribution to each project rather than claiming team work as your own.
- Review the submission and retain any application confirmation. Watch the platform and your registered contact details for the employer's response.
Jobsii does not collect applications for this opening. The application route is the employer's listing on Internshala, not an email address inferred from a company website. The notice does not publish a detailed test or interview sequence, so applicants should not rely on claims about guaranteed shortlisting, a fixed number of rounds or a particular assessment provider.
Preparing a relevant analytics application
The following preparation suggestions are Jobsii's editorial guidance, not additional employer requirements. Choose one compact project that follows a complete analysis process: define a question, identify the data, clean it, calculate relevant measures and explain the result. A small, accurate project with clear assumptions is more persuasive than a large dashboard whose figures cannot be traced back to source data.
For SQL, be ready to explain how you joined tables and prevented duplicate records from changing totals. For Excel, explain any validation, lookup or summary work you performed. If your project uses Python, include a readable notebook or script with the necessary steps and dependencies. For Power BI or Tableau, show how filters and date ranges affect a metric, rather than relying entirely on screenshots of polished visuals.
Communication deserves its own example. Prepare a short explanation of one finding for a person who does not use analytics tools. State what changed, how you checked it and what remains uncertain. This directly relates to the listing's report-writing and management-presentation responsibilities. Avoid adding confidential customer records or private employer data to a public portfolio; use an authorised or public dataset instead.
Questions worth asking before accepting
- Which team will supervise the internship, and what deliverables are expected during the first month?
- What are the working hours and meeting expectations across the five-day week?
- Which fixed stipend amount is being offered, and how are incentives calculated and paid?
- Will the employer provide required software access, and what equipment must the intern arrange?
- What conditions apply to completion certificates and recommendation letters?
These questions help distinguish the advertised opportunity from assumptions about remote work. They also make it easier to assess whether the role fits an applicant's timetable and learning priorities. Save the written offer and agreed terms; a social-media headline alone is not a substitute for employment or internship documentation.
Source and deadline reminder
The source for the vacancy, stipend, skills and application dates is the linked Internshala employer listing, checked on 25 September 2026. This is not a separately issued government or university notice. Apply by the displayed 21 October deadline and recheck the live page before submitting, because employers may update or close listings. No exact closing time is stated in the visible information reviewed, so avoid leaving the application until the last evening.
