Scaler Placement Outcomes: 89% of 12,851 Placed, Audited (2026)
Scaler's 3rd Placement Assessment Report is now out, with its findings independently evaluated by B2K Analytics. But what does that mean? And why should you trust the numbers in the report? That's exactly what we'll cover here.
For a student or a mid-career professional, it's already difficult to find programs that truly stand by their claims. And even if you do come across placement reports and salary figures, how do you know whether they're backed by a credible verification process? That's why the Scaler Placement Assessment Report underwent an independent evaluation by B2K Analytics, which followed an independent assessment methodology to review the reported data and evaluate the placement outcomes.
Scaler Placement Outcomes at a Glance
The table below summarises the key placement outcomes from the Placement Assessment Report. The findings have also been covered independently by Careers360.
| Modern Software & AI Engineering | Outcomes |
|---|---|
| Average CTC Before Upskilling | ₹11.8 LPA |
| Average CTC After Upskilling | ₹24.6 LPA |
| Average CTC Increment | 147% |
| Top 25% Average CTC | ₹45.6 LPA |
| Maximum Post-Scaler Salary | ₹1.4 Cr |
| Modern Data Science & ML | Outcomes |
|---|---|
| Average CTC Before Upskilling | ₹9.6 LPA |
| Average CTC After Upskilling | ₹21.1 LPA |
| Average CTC Increment | 149% |
| Top 25% Average CTC | ₹42.4 LPA |
| Maximum Post-Scaler Salary | ₹2.8 Cr |
You can download the complete Placement Assessment Report for a detailed breakdown of the methodology, salary distributions, and placement analysis.
The report covers 12,500+ learners from the 2024 - 2025 cohorts, with an overall placement rate of 89% across the assessed programs. Individual outcomes vary based on factors such as prior experience, technical skills, placement eligibility, interview performance, and market conditions.
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+1000 moreHow the Report Measures Placement: Methodology, Disclosed
Wondering what the scaler placement methodology includes? Here’s an overview.
| Methodology Parameter | Details |
|---|---|
| Assessment Period | 2024 - 2025 learner cohorts |
| Learners Assessed | 12,500+ learners |
| Assessment Agency | B2K Analytics |
| Data Source | Placement data, supporting information, and documentation provided by Scaler |
| Verification Method | 1:1 learner calls and offer letters |
| Sample Validation | Random sample verification of learner records |
| Assessment Type | Independent assessment |
The assessment methodology is published alongside the report so readers can understand how the placement outcomes were evaluated, what information was verified, and the scope of the assessment. The assessment has also been covered independently by BW People.
Also read: Scaler Academy Addressing High Fees, Placements & Transparency.
Salary Outcomes: Medians, Quartiles & the Honest Range
scaler placement report 2025, along with the 2024 cohort, included 12,500+ learners who completed the program. The report recorded an overall placement rate of 89% across the assessed cohort.
The report includes the scaler placement salary outcomes across different learner groups to show how career growth has varied across the assessed cohort. Along with the average CTC, it also highlights the top 25% and middle 80% salary outcomes for both programs.
For learners enrolled in the Modern Software & AI Engineering program, the average CTC increased from ₹11.8 LPA before joining Scaler to ₹24.6 LPA after placement, which is an average salary increment of 147%. Within this cohort, the top 25% reported an average CTC of ₹45.6 LPA, while the middle 80% reported ₹22.5 LPA.
Among Data Science & Machine Learning learners, the average CTC increased from ₹9.6 LPA to ₹21.1 LPA, with an average salary increment of 149%. The top 25% reported an average CTC of ₹42.4 LPA, while the middle 80% reported ₹18.2 LPA.
Career outcomes depend on several factors, including previous work experience, existing salary, interview performance, and hiring demand. Similar trends have also been observed in labour market research published by LinkedIn's Economic Graph.
Who Gets Placed: Eligibility & What It Actually Takes
The scaler placement eligibility depends on how prepared you are for the interviews and whether you have checked all the boxes of the set criteria. To become eligible for placement support, learners are expected to:
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Complete the core learning modules required as part of their program.
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Clear the readiness checks conducted during the program to demonstrate technical and interview preparedness.
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Actively participate in the placement process, including resume reviews, mock interviews, and company interview opportunities.
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Remain engaged throughout the hiring process, working with the career services team until interviews are completed.
Once these requirements are met, learners become eligible to enter Scaler's placement pool, where they receive placement assistance and access to hiring opportunities from Scaler's employer network. Since placements depend on interview performance, prior experience, role preferences, and hiring demand, becoming eligible for placement support should not be interpreted as a job guarantee.
Real Student Career Outcomes
Every learner starts from a different point in their career, so the outcomes naturally differ. Some join Scaler to transition into a new role, while others focus on building stronger fundamentals, preparing for interviews, or growing in their current careers. Here are two learner experiences.
1. Ashish Vitthal Mali
Electrical Engineering to Software Engineering at Red Hat
Ashish joined Scaler while transitioning from an Electrical Engineering background into Software Engineering. Although he was already working at Tata Consultancy Services, he wanted a more structured, industry-focused learning path to deepen his software engineering skills. He later transitioned to Red Hat.
2. Aman Singh
DevOps Engineer
For Aman, the value came from the learning experience and career preparation. He highlights the structured curriculum, mentorship, project guidance, and interview preparation that supported him throughout the program.
These are individual learner experiences, and outcomes naturally differ based on factors such as prior experience, career goals, interview performance, and market demand.
If you'd like to explore more learner journeys, you can read Scaler Placement Stories on Scaler's review page or browse independent reviews on Course Report, where Scaler currently holds an overall rating of 4.4/5.
How to Verify the Report Yourself
For anyone looking into Scaler placement verification, here are a few aspects you can independently review:
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Independent assessment: Check whether the placement report has been assessed by an external organisation.
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Assessment methodology: Review the reporting period, learner sample, and verification process used for the assessment.
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Independent coverage: See whether the assessment and its findings have been reported by external publications.
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Learner experiences: You can read reviews through various online platforms to understand experiences shared by different learners.
How Scaler Transformed Careers in Different Fields
Scaler learners achieved 2.5x salary growth with average post-Scaler CTC reaching ₹23L.
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Q1. Does Scaler guarantee a job?
No. Scaler provides placement support to learners who meet the program's eligibility criteria, but it does not guarantee a job. Final outcomes depend on factors such as technical skills, interview performance, prior experience, market demand, and the learner's participation in the placement process.
Turn Learning into Career Growth
Q2. Who audits Scaler's Placement Assessment Report?
Scaler's Placement Assessment Report was independently evaluated by B2K Analytics, the agency that also audits IIM Ahmedabad's placement reports. The assessment covered 12,500+ learners from the 2024 and 2025 cohorts and verified the reported placement outcomes using an independent methodology.
Q3. What salary do Scaler learners get?
According to Scaler's 3rd Placement Assessment Report, learners from the Modern Software & AI Engineering program reported an average post-upskilling CTC of ₹24.6 LPA, with the top 25% averaging ₹45.6 LPA. For the Modern Data Science & ML program, the average post-upskilling CTC was ₹21.1 LPA, while the top 25% averaged ₹42.4 LPA.
Q4. How long does it take to get placed through Scaler?
There isn't a standard placement timeline. Some learners transition quickly, while others, particularly career switchers or learners aiming for senior roles, may take longer. The time taken depends on the opportunities available and the learner's interview readiness.
Q5. What are the eligibility conditions for placement support?
Placement support is available to learners who meet the program's eligibility requirements. These generally include:
- Completing the required learning modules.
- Finishing the assigned projects and assessments.
- Meeting the program's placement readiness requirements.
- Actively participating in the placement process, including interviews and career support activities.
The exact eligibility criteria may differ across programs, so learners should refer to the latest program guidelines before enrolling.
Q6. Where can I verify these placement numbers independently?
The reported placement outcomes can be cross-checked through the independently assessed Placement Assessment Report, coverage by independent media publications, and learner reviews shared on various review platforms.
