The Data Behind NesaWorks: How We Benchmark Salaries

Every professional wants to know if they are paid fairly. But to answer that question, data integrity matters. At NesaWorks, Salary Worthiness Reports are not based on guesswork or random surveys. They are built on a foundation of verified datasets, AI-driven analysis, and analyst validation. This transparency is what sets us apart.

The Challenge of Salary Data

Salary data is notoriously messy. Job portals inflate numbers, surveys generalize averages, and personal anecdotes skew perceptions. This leaves professionals with incomplete or misleading benchmarks. NesaWorks solves this with a structured methodology.

Our Data Sources

NesaWorks aggregates data from multiple channels:

• Verified Market Surveys – Trusted compensation studies from industry research firms.
• Anonymized User Inputs – Contributions from thousands of professionals across India.
• Company Disclosures – Salary bands from public filings and HR benchmarking.
• Recruiter & Analyst Insights – Ground reality checks from hiring trends.

How We Process the Data

Step 1: Cleaning

Outliers, duplicates, and unverifiable entries are removed to ensure data quality.

Step 2: Normalization

Salaries are adjusted for location, company size, and role level — creating a fair baseline for comparison.

Step 3: AI Modeling

Machine learning models predict percentile ranges for roles based on experience, city, and skills. This ensures accuracy even in less-common roles.

Step 4: Analyst Validation

Human analysts review outputs, contextualizing anomalies (e.g., sudden fintech pay spikes) to ensure reports are not just data-driven but market-relevant.

Percentile Benchmarking Explained

Rather than giving one “average” number, NesaWorks shows:

• 10th Percentile – Entry-level or underpaid professionals
• 50th Percentile – The true market median
• 90th Percentile – Top earners in your role and location

This gives professionals clarity on where they stand and what to aim for.

Case Study: Role Benchmarking

A senior data scientist in Bangalore inputs her ₹22 LPA salary. The report shows the 50th percentile at ₹25 LPA and 90th at ₹32 LPA. This empowers her to negotiate with evidence rather than assumptions.

Why Our Method Is Superior

• Transparency – Clear methodology, not hidden averages.
• Relevance – Adjusted for city, company type, and skills.
• Dynamic Updates – Data refreshed quarterly to reflect market trends.

Global Comparisons

In the US, Levels.fyi became trusted by showing transparent salary bands. In India, NesaWorks brings the same rigor — but tailored for local contexts like tier-2 cities, hybrid work, and industry nuances.

The NesaWorks Edge

Our data is not static. It evolves with every new input and analyst validation. This means professionals using NesaWorks always work with the latest and most credible benchmarks.