Dashboard / Candidate

Arjun Verma

Placed in Product Manager by best fit (no role stated; scored higher on this rubric) · 04_arjun_verma.pdf

Private: squad_1@pg27.mesaschool.co · no phone found

Applied-role score

56/100

#7 of 34 PM applicants

PM score

56/100

SPM score

45/100

Current status

Analysed

Borderline (AI suggestion)

Your decision

Why they fit

Problem -> Change -> Result 25%
The CV presents multiple strong, concrete examples of the candidate identifying operational friction or workflow inefficiencies and delivering technical or UX changes that produced measurable improvements in adoption, overhead, and support volume.
Builds Repeatable Ways of Working 20%
The candidate has built repeatable operational methods and tools, including an internal automation tool that business team members adopted to save weekly reporting time, and standardized assessment scoring logic used across hiring rounds.

Where they fall short

Carries Ambiguous Problems Through to Closure −16 pts
The CV mentions serving as a cross-functional conduit between clients, end users, and engineering, but provides no specific example of navigating an ambiguous escalation or failure through to completion and follow-up.
Evidence-Led Decisions −12 pts
The candidate shows that feedback informed product fixes and dashboard iterations, but the CV does not show explicit trade-offs, rationale, or decisions being altered, deprioritised, or stopped based on evidence.
Gets to the Source Before Designing the Fix −12 pts
While the candidate analyzed aggregated feedback loops and user feedback, there is no evidence of directly observing, interviewing, or working alongside users to conduct firsthand discovery before shaping a solution.

Rubric breakdown: PM

PM (applied)SPM

Criterion	Weight	Score	Weighted	AI reasoning	Evidence from CV
Problem -> Change -> Result	25%	5/5	25.0/25	The CV presents multiple strong, concrete examples of the candidate identifying operational friction or workflow inefficiencies and delivering technical or UX changes that produced measurable improvements in adoption, overhead, and support volume.	“Analyzed cross-platform feedback loops to identify systemic friction points, leading to product fixes that reduced candidate support tickets by 50% (From 500+ to ~200/campaign).” “Engineered internal analysis automation using tools like Google Apps Script, MetaBase, Excel, etc. to aggregate platform performance metrics, saving the business team 15+ hours/week in manual reporting.” “Directed API-led integrations with SAP SuccessFactors, Workday and external vendors, automating candidate data synchronization and reducing manual recruiter overhead by 40%.” 1 AI quote(s) discarded: not found verbatim in CV
Evidence-Led Decisions	20%	2/5	8.0/20	The candidate shows that feedback informed product fixes and dashboard iterations, but the CV does not show explicit trade-offs, rationale, or decisions being altered, deprioritised, or stopped based on evidence.	“Analyzed cross-platform feedback loops to identify systemic friction points, leading to product fixes that reduced candidate support tickets by 50% (From 500+ to ~200/campaign).” “Scaled the Campus Ambassador Program to 130+ leads; utilized user feedback to iterate on internal ambassador dashboards, driving a 25% increase in engagement.”
Builds Repeatable Ways of Working	20%	4/5	16.0/20	The candidate has built repeatable operational methods and tools, including an internal automation tool that business team members adopted to save weekly reporting time, and standardized assessment scoring logic used across hiring rounds.	“Engineered internal analysis automation using tools like Google Apps Script, MetaBase, Excel, etc. to aggregate platform performance metrics, saving the business team 15+ hours/week in manual reporting.” “Standardized scoring logic across heterogeneous assessment types (Writing, Coding, Psychometric), ensuring "Apples-to-Apples" candidate comparison in high-stakes hiring rounds.”
Carries Ambiguous Problems Through to Closure	20%	1/5	4.0/20	The CV mentions serving as a cross-functional conduit between clients, end users, and engineering, but provides no specific example of navigating an ambiguous escalation or failure through to completion and follow-up.	“Acted as the primary conduit between 20+ Tier-1 corporate clients, the end users and the Engineering team.”
Gets to the Source Before Designing the Fix	15%	1/5	3.0/15	While the candidate analyzed aggregated feedback loops and user feedback, there is no evidence of directly observing, interviewing, or working alongside users to conduct firsthand discovery before shaping a solution.	“Analyzed cross-platform feedback loops to identify systemic friction points, leading to product fixes that reduced candidate support tickets by 50% (From 500+ to ~200/campaign).”
Total	100%		56	The candidate shows strong evidence of identifying operational and product bottlenecks to deliver measurable results, as well as building repeatable automations adopted by other teams. However, the CV lacks evidence of firsthand user observation, documented ambiguous problem closure, and explicit evidence-led decision trade-offs.

Scoring scale

0: No evidence in the CV
1: Indirect or participation-only evidence
2: Partial: some elements of the description, weak link to outcome
3: One clear example matching the description
4: Clear example with a visible result, candidate's own action linked to it
5: Repeated, strong examples fully matching the description, with results

Weighted contribution = score ÷ 5 × weight. Every quote is checked against the CV text; if none can be verified, the score is capped at 1.

Evidence

Verified CV quotes used (PM rubric)

“Analyzed cross-platform feedback loops to identify systemic friction points, leading to product fixes that reduced candidate support tickets by 50% (From 500+ to ~200/campaign).” · Problem -> Change -> Result
“Engineered internal analysis automation using tools like Google Apps Script, MetaBase, Excel, etc. to aggregate platform performance metrics, saving the business team 15+ hours/week in manual reporting.” · Problem -> Change -> Result
“Directed API-led integrations with SAP SuccessFactors, Workday and external vendors, automating candidate data synchronization and reducing manual recruiter overhead by 40%.” · Problem -> Change -> Result
“Analyzed cross-platform feedback loops to identify systemic friction points, leading to product fixes that reduced candidate support tickets by 50% (From 500+ to ~200/campaign).” · Evidence-Led Decisions
“Scaled the Campus Ambassador Program to 130+ leads; utilized user feedback to iterate on internal ambassador dashboards, driving a 25% increase in engagement.” · Evidence-Led Decisions
“Engineered internal analysis automation using tools like Google Apps Script, MetaBase, Excel, etc. to aggregate platform performance metrics, saving the business team 15+ hours/week in manual reporting.” · Builds Repeatable Ways of Working
“Standardized scoring logic across heterogeneous assessment types (Writing, Coding, Psychometric), ensuring "Apples-to-Apples" candidate comparison in high-stakes hiring rounds.” · Builds Repeatable Ways of Working
“Acted as the primary conduit between 20+ Tier-1 corporate clients, the end users and the Engineering team.” · Carries Ambiguous Problems Through to Closure
“Analyzed cross-platform feedback loops to identify systemic friction points, leading to product fixes that reduced candidate support tickets by 50% (From 500+ to ~200/campaign).” · Gets to the Source Before Designing the Fix

Outcomes stated in the CV

Automated screening for 1.5L+ candidates and reduced time-to-screen by 70% for enterprise clients via Unified AI Assessment Engine.
Onboarded 200+ colleges and facilitated 2.6M+ student registrations via the TPO Tracking Dashboard.
Drove a 20% growth in recruiter adoption and a 30% reduction in time-per-action through redesign of the Recruiter Journey & Panels.
Reduced candidate support tickets by 50% (from 500+ to ~200/campaign) through systemic friction fixes.
Cut platform testing time by 30% by spearheading an Activity Logs Architecture.
Saved business team 15+ hours/week in manual reporting by engineering automated performance metric reporting.

Anonymised CV (exactly what the AI saw)

New Delhi, Delhi, India
SUMMARY
Data-driven Associate Product Manager with 2+ years of experience in the B2B SaaS and Assessment Tech domain, specializing in scaling
candidate lifecycle management systems. Proven track record of scaling platforms to 2.6M+ users and driving a 20% increase in recruiter
adoption through data-driven redesigns and API integrations. Proficient in translating complex enterprise requirements into scalable system
architectures. Technical edge in SQL, API-first design, and Agentic AI workflows.
EXPERIENCE
Associate Product Manager
Unstop March 2025 - Present New Delhi, Delhi, IN,
• Unified AI Assessment Engine: Orchestrated a high-scale evaluation ecosystem integrating AI Screening, CEFR-calibrated Speech
Analytics, and Secure Proctoring; automated screening for 1.5L+ candidates and achieved a 70% reduction in time-to-screen for enterprise
clients.
• Product-Led Growth (PLG): Launched the TPO Tracking Dashboard, enabling institutional scale by onboarding 200+ colleges and
facilitating 2.6M+ student registrations.
• Product Adoption & UX Architecture: Led the end-to-end redesign of the Recruiter Journey & Panels; optimized navigation and candidate-
listing visibility, resulting in a 20% growth in recruiter adoption and a 30% reduction in time-per-action.
• Enterprise Roadmap Delivery: Managed the delivery of 100+ custom features for marquee clients like Flipkart, Adobe, Indigo, etc., including
complex customizable workflows and multi-round automated pipelines.
• System Interoperability: Directed API-led integrations with SAP SuccessFactors, Workday and external vendors, automating candidate data
synchronization and reducing manual recruiter overhead by 40%.
Associate, Quality Assurance Engineer
Unstop March 2024 - March 2025 New Delhi, Delhi, IN,
• User Experience Optimization: Analyzed cross-platform feedback loops to identify systemic friction points, leading to product fixes that
reduced candidate support tickets by 50% (From 500+ to ~200/campaign).
• Unified Audit Architecture: Spearheaded the mapping of an "Activity Logs Architecture", mapping every candidate or recruiter state transition
to a single audit trail, cutting platform testing time by 30%.
• Evaluation Normalization: Standardized scoring logic across heterogeneous assessment types (Writing, Coding, Psychometric), ensuring
"Apples-to-Apples" candidate comparison in high-stakes hiring rounds.
Associate, Business and Website Operations
Unstop July 2023 - March 2024 New Delhi, Delhi, IN,
• Process Automation: Engineered internal analysis automation using tools like Google Apps Script, MetaBase, Excel, etc. to aggregate
platform performance metrics, saving the business team 15+ hours/week in manual reporting.
• Community Growth: Scaled the Campus Ambassador Program to 130+ leads; utilized user feedback to iterate on internal ambassador
dashboards, driving a 25% increase in engagement.
• Cross-Stakeholder Collaboration: Acted as the primary conduit between 20+ Tier-1 corporate clients, the end users and the Engineering
team.
SKILLS
Product Strategy: Product Roadmapping, Product-Led Growth (PLG), Backlog Prioritization, Competitor Benchmarking, PRD/User Story
Authoring
Product Discovery: User Research, A/B Testing, MS Clarity, Root Cause Analysis, Wireframing (Figma)
Languages and Tools: SQL, Python, MS Excel, Google Analytics, MoEngage, Power BI, MetaBase, Figma, Miro, Mermaid.js, Jira, ClickUp,
MATLAB
Collaboration and Delivery: Agile, Scrum, Kanban, Cross-functional Leadership, Stakeholder Management
Technical: API Integration (REST), Microservices, Generative & Agentic AI, Selenium, AWS
EDUCATION
Bachelors of Sciences (Hons.) in Electronics and Communications
Minor in Mathematics • Sri Venkateswara College, University of Delhi • New Delhi, Delhi, IN • 2023
INVOLVEMENT
President, NSS unit of Sri Venkateswara College
New Delhi, Delhi, IN • National Service Scheme • September 2021 - July 2023
• Led a cross-functional team of 120+ volunteers across 6 specialized wings to execute 40+ large-scale events, successfully serving a
community of 5,000+ participants.
• Directed 5 flagship initiatives in education and healthcare for marginalized communities, overseeing end-to-end logistics, resource
budgeting, and volunteer training modules.
[CANDIDATE] VERMAArjun [CANDIDATE]
[EMAIL REDACTED] +91 98674 2019398674 20193 [CANDIDATE]-[CANDIDATE]-pmin/[CANDIDATE]-[CANDIDATE]-pm

Redacted: name ×6, email ×1

Interview brief

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Email draft

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Audit trail (3)

9/29/2026, 11:35:22 AMsystemanalysis completed{"PM_score":56,"SPM_score":45}
9/29/2026, 11:35:22 AMsystemrole assigned best fit{"role":"PM","PM_score":56,"SPM_score":45}
9/29/2026, 11:29:27 AMsystemcv ingested{"file":"04_arjun_verma.pdf","role":"AUTO","redactions":{"name":19,"email":1},"name_detected":true}