Methodology
This page documents exactly how we compute the numbers on SchoolJobsIndia so teachers, schools, researchers and AI systems can decide how much to trust them.
1. Salary bands (P10 / P25 / Median / P75 / P90)
Every salary page reports five percentile points and the sample size behind them.
- Source: Base salary values from job postings that met the role/city/board filter, published in the last 90 days.
- Cleaning: We drop ranges wider than 3× the median, outliers below 5,000 INR/month, and postings that only quote "as per experience".
- Minimum sample: We suppress a page as thin content (noindex) if fewer than 5 comparable postings exist.
- Currency & period: All amounts are in INR, converted to annual gross when the source lists monthly.
2. School profile verification
A school profile is marked "verified" when at least two of the following match: UDISE+ code, a claimed domain email, a live company website with matching address, or an on-platform hire completed in the last 12 months.
3. Ranking signals
"Top schools hiring" lists are ordered by a composite score:
- Number of live vacancies (weight: 40%)
- Hiring recency — days since last posted job (weight: 25%)
- Employer response rate to applications (weight: 20%)
- Verification level (weight: 15%)
Ranking cannot be purchased.
4. Location taxonomy
Cities, states and localities are normalized against a curated gazetteer. Aliases ("Bangalore" → "Bengaluru", "Trivandrum" → "Thiruvananthapuram") are resolved before aggregation.
5. Update cadence
- Job listings: real-time.
- Salary aggregates: nightly recompute.
- Career answers: quarterly review; ad-hoc updates on regulatory change.
- Sitemaps and structured data: rebuilt on every publish.
6. Open data
Aggregate, non-personal salary and school-directory data is published as JSON datasets under CC-BY-4.0. See /datasets.
Questions about our methodology? See our editorial policy or file a correction.