What the Ghaziabad placement data can and cannot show
For applicants comparing Jaipuria Institute of Management in Ghaziabad for the 2027 intake, the strongest cohort-level evidence I found is the institute's NIRF 2026 Management submission. It identifies the reporting institution as Jaipuria Institute of Management, institute code IR-M-C-46123, and labels the outcomes as postgraduate two-year programmes. The latest completed cohort in that submission is 2024-25. These are historical reported outcomes, not a forecast for students entering in 2027, and they should not be mixed with figures for Jaipuria's Jaipur, Noida or Lucknow campuses.
NIRF-reported outcomes for two-year postgraduate programmes
The source's group label is “PG [2 Years Program(s)]”. It does not split the figures by MBA specialisation, so these rows cannot show whether Finance, Marketing, Human Resources, Business Analytics or another study path had a different result. The report also does not provide the number of students eligible for placement, the number who registered, opt-outs, offer counts, or a formula for a placement rate. Its “placed” count is therefore best read beside the stated graduates-in-minimum-time count, not converted into an official placement percentage.
For a simple comparison, dividing placed students by graduates in minimum stipulated time gives 95.9% in 2022-23, 95.8% in 2023-24 and 91.9% in 2024-25. These are Admission Guardian calculations from the two NIRF columns, rounded to one decimal place. They describe only the relationship between those reported counts. They are not the institute's stated placement rates and do not establish the outcome for every graduate or every student seeking a job.
The counts increased over the three reported years: 194 to 284 graduates in minimum time, and 186 to 261 placed students. The median salary moved from ₹6.03 lakh to ₹6.09 lakh, then to ₹6.00 lakh. That is a narrow ₹9,000 range across the reported years, rather than a sustained upward trend. The report labels the measure “Median salary of placed graduates” and gives an amount in rupees; it does not define whether the amount is fixed pay, total CTC, or another compensation basis. It should not be called an average or a highest package.
The same NIRF table records 6, 7 and 23 students selected for higher studies in the three respective graduating years. This is a separate reported destination count, not a count of students who received placement offers. NIRF's placement table covers the PG two-year group. It does not establish outcomes for a specific specialisation, a summer internship cohort, or the institute's entire multi-campus group.
Roles, sectors and recruiter evidence
Jaipuria's placement brochure for 2024-26 presents a “Final Placements Batch 2023-25 at a Glance” and reports 170 participating companies. It identifies consultancy as the highest recruiting sector and Associate HR and Management Trainee as the leading job-role categories in that snapshot. The brochure's company figure is not a student or offer denominator, and the role labels do not reveal how many students entered each role. Treat them as a description of that brochure's placement snapshot, not as a promise or a specialization-wise outcome table.
The institute's current Ghaziabad placement page describes roles across Consulting and Research, Fintech, IT, Manufacturing, Market Intelligence and Analytics, Real Estate, Services, Hospitality, Logistics and Retail. Examples include Research Associate, Management Trainee, Credit Analyst, Relationship Manager and Data Analyst. Its recruiter gallery displays names including Yes Bank and Deloitte. These are examples of the roles and recruiter range shown by the institution; the page does not attach a student count or offer total to each name.
A separate Top Placements 2024-26 page displays individual examples, including Research Associate (Primary), Deputy Manager, Management Trainee and Customer Service Manager. An individual profile or employer logo is not a cohort-wide placement result. In particular, a selected profile cannot be used to estimate the typical role, the chance of receiving an offer, or salary for an incoming student.
There is a caution within the institute's own online presentation: the placement page says 60% of placements are in BFSI and Consulting, but its sector-wise widget shows 0% beside its sector labels. Because those displays conflict, I have not used a sector percentage to compare Ghaziabad outcomes. The brochure's qualitative claim that consultancy was the top recruiting sector is reported with its own 2023-25 snapshot label instead.
How an applicant should use these figures
The NIRF figures are the most useful evidence here for comparing the number of graduates, placed students and median salary across identified cohorts. Their limits matter just as much: the source does not state the eligible-for-placement denominator or compensation definition, and its PG two-year grouping does not separate the institute's named MBA pathways. The median describes the middle salary among those reported as placed; it does not mean that each student can expect that amount.
Before using a placement number in a return-on-cost calculation, ask the Ghaziabad campus for a report covering the exact programme and batch. Ask how many students were eligible and registered, how many were placed, how students with multiple offers are counted, and whether the salary is annual fixed pay or total CTC including variable components. Request the date on which the results were finalised and whether internships are reported separately. Those details would make a newer campus report more comparable with the published NIRF cohorts.
For a 2027 applicant, the evidence supports a qualified conclusion: Jaipuria Ghaziabad has submitted recent cohort-level PG two-year results, and its own materials show recruitment across several sectors and role types. The published evidence does not establish a guaranteed offer, a 2027 placement rate, a specialisation-level median, or a directly comparable salary basis. Use the cohort table as a historical baseline, then seek programme-specific and denominator-defined figures before treating it as a personal outcome estimate.