Dashboard / Candidate
Rohan Sane
Applied for Product Manager · pm_10_rohan_sane.pdf
Private: squad_4@pg27.mesaschool.co · +91 93720 84315
Applied-role score
72/100#5 of 34 PM applicants
PM score
72/100SPM score
43/100Current status
AnalysedRecommend shortlist (AI suggestion)
Your decision
1
Why they fit
- Problem -> Change -> Result 25%
The candidate provides multiple strong examples where they identified a friction point, delivered a product change, and achieved quantifiable business outcomes, such as reducing onboarding time and manual intervention.
- Evidence-Led Decisions 20%
The candidate explicitly demonstrates evidence-led decision-making where experimental data directly altered product release decisions. However, detailed post-decision results for those specific altered releases are not elaborated beyond the counts.
- Gets to the Source Before Designing the Fix 15%
The CV provides repeated, strong examples of firsthand user research (interviews with brand operations managers and on-the-ground delivery partners) directly shaping subsequent product redesigns and delivering measurable results.
2
Where they fall short
- Carries Ambiguous Problems Through to Closure −16 pts
The CV shows proactive collaboration with client success to prevent escalations, but lacks any concrete example of driving a messy, multi-functional issue or escalation from identification through to post-resolution closure.
| Criterion | Weight | Score | Weighted | AI reasoning | Evidence from CV |
|---|---|---|---|---|---|
| Independent Decision Ownership | 30% | 1/5 | 6.0/30 | The CV provides only indirect evidence of decision ownership, noting that the candidate works with a PM Lead above and operates independently on day-to-day decisions. It lacks any specific example of making consequential calls under uncertainty or managing trade-offs independently. |
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| Problem -> Change -> Business/Operational Result | 20% | 5/5 | 20.0/20 | The candidate provides multiple clear, quantified examples linking their interventions directly to operational and customer outcomes, including reducing manual interventions by 28%, cutting onboarding time from 3 weeks to 4 days, and decreasing task completion time by 22%. |
|
| Evidence-Led Prioritisation and Reversal | 20% | 2/5 | 8.0/20 | The candidate mentions running A/B experiments that changed release decisions and using interview/research findings to drive redesigns. However, there is no detailed narrative explaining the specific evidence and how an earlier direction was reversed or materially altered. |
|
| Creates Systems Others Run | 15% | 2/5 | 6.0/15 | The CV notes that the candidate built an A/B testing framework from scratch and established regular sessions with the client success team. However, there is no evidence showing that these systems were adopted or maintained by others independently beyond the candidate's own execution. |
|
| Multi-Party Resolution Under Pressure | 15% | 1/5 | 3.0/15 | There is only indirect evidence regarding escalation prevention via regular sessions with client success. The CV contains no evidence of directly driving high-pressure incidents, post-mortems, or multi-stakeholder resolutions through to closure. |
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| Total | 100% | 43 | The candidate demonstrates strong execution ability with repeated, quantified operational impacts from their feature deliveries. However, the profile shows minimal evidence of independent consequential decision ownership, system creation that others run, or resolving complex multi-party issues under pressure. | ||
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.
4
Evidence
Verified CV quotes used (PM rubric)
- “Redesigned the exception management dashboard based on 20+ discovery interviews with brand operations managers; reduced operations team's daily manual intervention by 28%” · Problem -> Change -> Result
- “Shipped a bulk order upload and validation feature that reduced client onboarding time from 3 weeks to 4 days” · Problem -> Change -> Result
- “Led a UX research initiative with 30 delivery partners across Mumbai and Bengaluru — findings drove a navigation redesign that reduced task completion time by 22%” · Problem -> Change -> Result
- “Built the team's A/B testing framework from scratch; ran 6 experiments in the first 8 months, 3 of which changed release decisions” · Evidence-Led Decisions
- “Built the team's A/B testing framework from scratch; ran 6 experiments in the first 8 months, 3 of which changed release decisions” · Builds Repeatable Ways of Working
- “Runs regular sessions with the client success team to surface operational complaints before they become escalations” · Builds Repeatable Ways of Working
- “Runs regular sessions with the client success team to surface operational complaints before they become escalations” · Carries Ambiguous Problems Through to Closure
- “Redesigned the exception management dashboard based on 20+ discovery interviews with brand operations managers; reduced operations team's daily manual intervention by 28%” · Gets to the Source Before Designing the Fix
- “Led a UX research initiative with 30 delivery partners across Mumbai and Bengaluru — findings drove a navigation redesign that reduced task completion time by 22%” · Gets to the Source Before Designing the Fix
Outcomes stated in the CV
- Reduced operations team's daily manual intervention by 28% via exception management dashboard redesign
- Reduced client onboarding time from 3 weeks to 4 days with bulk order upload and validation feature
- Reduced delivery partner task completion time by 22% through UX research-driven navigation redesign
- Ran 6 experiments via a newly built A/B testing framework, changing 3 release decisions
Anonymised CV (exactly what the AI saw)
[CANDIDATE] Product Manager [PHONE REDACTED] · [EMAIL REDACTED] · Bengaluru · [PROFILE URL REDACTED] Professional Summary Product Manager with 3 years in B2B SaaS and marketplace products. Strong in discovery, analytics, and cross-functional execution. Worked on products for enterprise operations teams — understand how complex workflows translate into software requirements. Good at shipping and measuring. Have not worked in logistics directly but have built for operational users. Work Experience Product Manager Shadowfax Technologies (Logistics & Delivery SaaS, 500+ employees), Bengaluru · Jan 2023 – Present — PM for the client-facing order management and tracking module — 300+ brand and enterprise clients use the platform — Redesigned the exception management dashboard based on 20+ discovery interviews with brand operations managers; reduced operations team's daily manual intervention by 28% — Shipped a bulk order upload and validation feature that reduced client onboarding time from 3 weeks to 4 days — Works within a 4-person PM team; owns this module with a PM Lead above; operates independently on day-to-day decisions — Runs regular sessions with the client success team to surface operational complaints before they become escalations Associate Product Manager Shadowfax Technologies, Bengaluru · May 2021 – Dec 2022 — Supported PM on the delivery partner app — owned 4 features from PRD to release across 18 months — Led a UX research initiative with 30 delivery partners across Mumbai and Bengaluru — findings drove a navigation redesign that reduced task completion time by 22% — Built the team's A/B testing framework from scratch; ran 6 experiments in the first 8 months, 3 of which changed release decisions Education B.Tech, Computer Science · Symbiosis Institute of Technology, Pune · 2017–2021 · CGPA 8.2/10 Skills & Certifications Product management · Delivery & logistics platforms · A/B testing · JIRA · Figma · SQL · Amplitude · Metabase · Notion Product Analytics – Amplitude Certification (2022)
Redacted: name ×1, email ×1, phone ×1, profile url ×1
5
Interview brief
Briefs are written when you shortlist a candidate.
6
Email draft
An offer or rejection draft is prepared once you make a decision. Nothing is ever sent without your approval.
Audit trail (2)
- 9/29/2026, 11:02:20 AMsystemanalysis completed{"PM_score":72,"SPM_score":43}
- 9/29/2026, 11:01:27 AMsystemcv ingested{"file":"pm_10_rohan_sane.pdf","role":"PM","redactions":{"name":1,"email":1,"phone":1,"profile_url":1},"name_detected":true}