ResumeGrade
For placement & training cells

Placement readiness for universities,
measured.

ResumeGrade gives training & placement cells a defensible, rubric-based score for every student resume, across 1,000+ students, graded in the time it takes to review one by hand.

DPDP-aligned, Indian data residencyBuilt on Harvard Career Services principlesRubric transparency, no black box
01 · The problem

A TPO reviews 3,000 resumes before drive season.

Most get a 90-second glance. Feedback is inconsistent across faculty reviewers. Weak resumes reach recruiters first. Strong students get missed. Placement rates suffer. The placement office carries the blame.

90s
Median review time per resume, done by hand
37%
Students flagged as "not ready" after mock drives
11 days
Median turnaround for a cohort of 500
02 · How it works

Three steps. One afternoon. One thousand students.

STEP 01

Upload the cohort

Bulk upload via CSV, Drive, or your existing placement portal. Works with Superset, Zoho Recruit, and your TPO software.

cohort_cse_2026.csv
001 Arjun Mcv.pdf
002 Riya Patelcv.pdf
003 Karthik Rcv.pdf
004 Ananya Scv.pdf
005 … 312 rowscv.pdf
STEP 02

Grade against your rubric

Start from the ResumeGrade default (built on Harvard Career Services principles) or upload your own. Weight six axes per cohort or per JD.

rubric · default + SDE-intern weights
Evidence22%
Structure18%
Skills15%
JD align20%
Role fit13%
Complete12%
STEP 03

Return with receipts

Each student gets a 0 to 100 score, score band badge, and 8 to 14 specific edits. No vague tips. Audit log for every mark.

REWRITE"Worked on backend" → "Shipped 3 Django APIs at 40k req/day"
MISSINGAdd quantified impact to GDSC lead role
FORMATDates right-align, inconsistent across sections
03 · The rubric

Six dimensions. One score. No black box.

Every student score breaks down into the same six dimensions. When you defend a decision in front of management, or when a student asks why they read 51, the answer is on the page.

01
Structure
ATS-parseable, hierarchy intact, no formatting traps
83/100
02
Evidence
Quantified outcomes, verified projects, ownership signals
58/100
03
Skills
Stack mapped to claim depth: beginner, fluent, shipping
71/100
04
Role fit
Match to function, not just keywords
76/100
05
JD alignment
Re-scored per role uploaded by your TPO
71/100
06
Completeness
Mandatory institutional fields present
89/100
Why this rubric

Built on the principles placement teams already trust.

The rubric is anchored in the same heuristics Harvard Career Services and top campus recruiters use to triage at scale. We publish the weighting, the dimension definitions, and the scoring model. When a principal asks “why did this score 58 and that 71,” there is a paper trail, not a vibe.

“Standardise → Align → Prove readiness. Every step is documented, every decision auditable. That is the difference between a tool you trust with NAAC and a tool you trust with a screenshot.”

— RG Methodology, v3.2

See the difference the rubric makes.

Student resume before ResumeGrade feedback: weak structure, no quantified impact
Student resume after ResumeGrade feedback: clear structure, quantified bullets, ATS-ready

Drag the divider to compare.

Everything placement teams need to manage resume quality at scale

Built for Placement Teams, Not Just Students

Everything placement leadership needs to turn prep into a managed system. Roadmap items scale with your rollout.

Dashboard for placement officers

Track student uploads, scores, and batch progress, and see who needs support early.

Batch analytics

Average scores by batch, department, or intake, and compare terms over time.

Standardisation

One quality bar across departments so advising and training stay aligned.

Bulk analysis

Review many files without opening each resume manually, at scale for large batches.

Progress tracking

Score improvement over time as students iterate before placement season.

Institutional rollout

From pilot to campus wide tiers, built for governance and procurement conversations.

Advisor & student nudges

Email style prompts when drafts stall or scores drop, without manual chasing.

Exports & reporting

CSV and summary views for leadership reviews, accreditation, and partner updates.

No more spreadsheets. No more guessing in October.

Batch Scores. Gap Flags. Early Enough to Act.

See batch level signals and student level actions in one place, so leadership can steer prep before placement season peaks.

Identify which students are ready, and who needs support, instantly.

Batch scorecards

Track average scores, batch trends, and who still needs support, without opening hundreds of PDFs by hand.

Average readiness score

Rolling batch view: compare departments or intakes at a glance.

2026 batchCS deptExport

JD alignment coverage

Share of students who matched a target role before applying.

JD matchKeywordsSkills

From score to action

Scores tie to line level feedback and a ranked action list, so students know what to fix next, and advisors can intervene early.

Top actions

Done: Quantify impact

3 bullets flagged

ATS scan
0 to 100 rubric

Batch trends

Resume quality and shortlisting readiness rise together: compare batches and terms on one view.

Scoring + JD fabric

0 to 100 rubric, line feedback, and JD match live in one workflow, with no brittle handoffs between tools.

Human-in-the-loop

Advisors add reviews and nudges where it matters, without rereading every draft line by line.

Students who follow structured resume systems and tailor materials to specific roles are typically better positioned to pass first round screening. The exact lift depends on your batch and labour market.

Frequently asked questions

See Batch Readiness Before the First Drive

Book a walkthrough or start a pilot. We'll align to your academic calendar.