Dashboard / Candidate

Tanvi Jain

Applied for Product Manager · pm_15_tanvi_jain.pdf

Private: squad_3@pg27.mesaschool.co · +91 90082 29415

Applied-role score

32/100

#25 of 34 PM applicants

PM score

32/100

SPM score

22/100

Current status

Analysed

Below shortlist (AI suggestion)

Your decision

Why they fit

Problem -> Change -> Result 25%
The candidate automated 14 recurring reports using Python and SQL, directly resulting in reducing the sales team's weekly reporting effort by 8 hours. The candidate's specific action is clearly tied to a measurable operational improvement.

Where they fall short

Carries Ambiguous Problems Through to Closure −20 pts
There is no evidence in the CV of taking an ambiguous problem through cross-functional resolution, handling escalations, or managing post-resolution follow-ups.
Evidence-Led Decisions −16 pts
The candidate conducted funnel analyses and presented findings to leadership, but explicitly notes they held no decision-making ownership. There is no evidence showing what decisions were made, changed, or prioritized based on that data.
Gets to the Source Before Designing the Fix −15 pts
There is no evidence in the CV of firsthand discovery, user interviews, shadowing, or directly observing users to shape a fix or product change.

Rubric breakdown: SPM

PM (applied)SPM

Criterion	Weight	Score	Weighted	AI reasoning	Evidence from CV
Independent Decision Ownership	30%	0/5	0.0/30	The CV shows no evidence of independent decision ownership. In fact, it explicitly notes that the candidate had no direct product ownership and that decisions were owned by the PM team.	Evidence not present in the CV.
Problem -> Change -> Business/Operational Result	20%	3/5	12.0/20	The candidate provides one clear operational example where automating recurring reports reduced weekly reporting effort by 8 hours. However, there are no other examples linking candidate-led changes to business or customer metrics.	“Automated 14 recurring reports using Python and SQL; reduced the team's weekly reporting effort by 8 hours”
Evidence-Led Prioritisation and Reversal	20%	1/5	4.0/20	The candidate provided analytical support and presented findings to leadership, but did not own prioritisation decisions or execute reversals based on evidence.	“Ran SQL-based funnel analysis for the ad auction and targeting features; findings presented monthly to the product leadership team” “No direct product ownership — role is analytical support for product managers; decisions on what to build owned by PM team”
Creates Systems Others Run	15%	2/5	6.0/15	The candidate created measurement frameworks and automated reporting used by sales teams, but the evidence shows the candidate continuing to maintain dashboards rather than embedding systems that others independently operate.	“Built and maintained the product analytics infrastructure for InMobi's publisher monetisation platform — 200+ dashboards across 12 product areas” “Defined measurement frameworks for 8 product launches; worked with PMs to set success metrics and track outcomes post-launch”
Multi-Party Resolution Under Pressure	15%	0/5	0.0/15	There is no evidence in the CV of driving multi-party resolutions, managing escalations, or resolving issues under pressure.	Evidence not present in the CV.
Total	100%		22	The candidate has a background as a data and product analyst and explicitly lacks product decision ownership. While there is evidence of building analytics frameworks and report automation, the CV does not demonstrate the core Senior Product Manager rubric criteria around independent decisions, evidence-led reversals, or cross-functional resolution 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.

Evidence

Verified CV quotes used (PM rubric)

“Automated 14 recurring reports using Python and SQL; reduced the team's weekly reporting effort by 8 hours” · Problem -> Change -> Result
“Ran SQL-based funnel analysis for the ad auction and targeting features; findings presented monthly to the product leadership team” · Evidence-Led Decisions
“No direct product ownership — role is analytical support for product managers; decisions on what to build owned by PM team” · Evidence-Led Decisions
“Defined measurement frameworks for 8 product launches; worked with PMs to set success metrics and track outcomes post-launch” · Builds Repeatable Ways of Working
“Automated 14 recurring reports using Python and SQL; reduced the team's weekly reporting effort by 8 hours” · Builds Repeatable Ways of Working

Outcomes stated in the CV

Built 200+ dashboards across 12 product areas for publisher monetisation platform
Defined measurement frameworks for 8 product launches
Automated 14 recurring reports, reducing weekly reporting effort by 8 hours

Anonymised CV (exactly what the AI saw)

[CANDIDATE]
[PHONE REDACTED] · [EMAIL REDACTED] · Bengaluru
[PROFILE URL REDACTED]
PROFESSIONAL SUMMARY
Transitioning from a data analyst background into product management. 4 years of experience building analytics
infrastructure and BI dashboards for product and marketing teams. Strong in data, SQL, and defining metrics. Now
looking to own the product side — not just measure it. Completed a product management certification programme
in 2024.
WORK EXPERIENCE
Product Analyst → Senior Product Analyst
InMobi (Mobile Advertising Platform, 1000+ employees), Bengaluru · Jul 2020 – Present
— Built and maintained the product analytics infrastructure for InMobi's publisher monetisation platform — 200+
dashboards across 12 product areas
— Defined measurement frameworks for 8 product launches; worked with PMs to set success metrics and track
outcomes post-launch
— Ran SQL-based funnel analysis for the ad auction and targeting features; findings presented monthly to the product
leadership team
— No direct product ownership — role is analytical support for product managers; decisions on what to build owned by
PM team
— Completed Product School PM Certification in Jan 2024 as a step toward transitioning into a PM role
Data Analyst
PubMatic (Programmatic Advertising), Pune · Jun 2018 – Jun 2020
— Built advertiser performance reports and yield optimization dashboards for the India sales team
— Automated 14 recurring reports using Python and SQL; reduced the team's weekly reporting effort by 8 hours
EDUCATION
B.Tech, Computer Science · BIT Mesra, Ranchi · 2014–2018 · CGPA 7.8/10
SKILLS & CERTIFICATIONS
SQL · Python · Tableau · Metabase · Google Analytics · JIRA · Product analytics · A/B test analysis · Figma (basic)
Product School PM Certification (2024) · Google Data Analytics Certificate (2022)

Redacted: name ×1, email ×1, phone ×1, profile url ×1

Interview brief

Briefs are written when you shortlist a candidate.

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, 11:02:34 AMsystemanalysis completed{"PM_score":32,"SPM_score":22}
9/29/2026, 11:01:28 AMsystemcv ingested{"file":"pm_15_tanvi_jain.pdf","role":"PM","redactions":{"name":1,"email":1,"phone":1,"profile_url":1},"name_detected":true}