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Arnav Sen

Placed in Senior Product Manager by best fit (no role stated; scored higher on this rubric) · 03_arnav_sen.pdf
Private: squad_1@pg27.mesaschool.co · no phone found
Applied-role score
36/100
#11 of 16 SPM applicants
PM score
29/100
SPM score
36/100
Current status
Analysed
Below shortlist (AI suggestion)
Your decision
1

Why they fit

No criterion reached a clear-evidence score (3/5 or higher) on the SPM rubric.

2

Where they fall short

  • Independent Decision Ownership −18 pts

    The candidate notes broad responsibility for trade-offs and acting as a primary decision interface across stakeholders. However, the CV lacks specific, detailed examples of consequential decisions made independently under uncertainty and their resulting consequences.

  • Evidence-Led Prioritisation and Reversal −16 pts

    The CV contains high-level mentions of roadmap prioritization and discovery analysis, but offers no specific example of using evidence to prioritize or stop an initiative. There is no evidence of a reversal or material alteration of direction based on data.

  • Problem -> Change -> Business/Operational Result −12 pts

    The candidate links interventions in calculation areas and discovery practices to qualitative results such as platform stability and reduced rework. However, there is no quantified business or operational outcome provided anywhere in the CV.

3

Rubric breakdown: PM

CriterionWeightScoreWeightedAI reasoningEvidence from CV
Problem -> Change -> Result25% 2/510.0/25The candidate reports introducing structured discovery practices that reduced delivery risk and rework. However, the CV lacks a detailed, concrete description of the initial friction and does not provide specific measurable metrics for the outcome.
  • “Reduced downstream delivery risk and rework by introducing AI-augmented structured discovery and solution evaluation practices.”
  • “Enabled delivery of regulatory and business-critical changes in complex calculation areas without compromising platform stability.”
Evidence-Led Decisions20% 1/54.0/20The CV mentions balancing roadmap constraints, CAB forums, and trade-off evaluations, but does not present a concrete example of a decision being changed, stopped, or prioritized based on specific operational or user data.
  • “Owned prioritization and roadmap inputs, balancing business value, regulatory risk, system stability, and delivery constraints across releases.”
  • “Led product discovery and decision-making through stakeholder workshops, CAB forums, AI-assisted impact analysis, and cross-functional alignment across business, compliance, and technology teams.”
Builds Repeatable Ways of Working20% 2/58.0/20The candidate notes introducing AI-augmented discovery and evaluation practices, as well as strengthening delivery governance. However, the evidence remains partial because it does not detail a specific tool, template, or repeatable mechanism that other teams explicitly adopted and reused.
  • “Reduced downstream delivery risk and rework by introducing AI-augmented structured discovery and solution evaluation practices.”
  • “Contributed to enterprise-scale delivery governance by strengthening requirement clarity, traceability, and defect containment practices.”
Carries Ambiguous Problems Through to Closure20% 1/54.0/20The CV contains high-level claims about owning ambiguous problems and driving high-risk changes across multi-region stakeholders. It lacks a specific example of managing an escalation or messy multi-functional problem from identification through to post-resolution follow-up.
  • “Proven track record of owning ambiguous problems, leading cross-functional and multi-region stakeholders, and delivering scalable solutions through clear trade-offs and pragmatic decision-making.”
  • “Drove high-risk change initiatives in complex calculation and workflow areas by leveraging AI-assisted evaluation of solution options, surfacing trade-offs, and protecting downstream system integrity.”
Gets to the Source Before Designing the Fix15% 1/53.0/15The CV lists stakeholder workshops and UAT collaboration, but provides no evidence of directly observing or interviewing end users experiencing friction. There is also no example showing that the designed solution changed as a direct result of firsthand discovery.
  • “Led product discovery and decision-making through stakeholder workshops, CAB forums, AI-assisted impact analysis, and cross-functional alignment across business, compliance, and technology teams.”
  • “Hands-on experience in UAT support, working closely with business stakeholders to validate critical workflows and ensure release readiness”
Total100%29The candidate shows extensive background leading delivery and platform initiatives across complex, regulated enterprise environments. However, the CV is framed predominantly around high-level responsibilities and general claims rather than concrete examples showing evidence-based decision pivots, firsthand discovery, or repeatable frameworks adopted by others. Consequently, the profile presents limited specific evidence across the rubric's core PM competencies.
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 (SPM rubric)
  • “Owned prioritization and roadmap inputs, balancing business value, regulatory risk, system stability, and delivery constraints across releases.” · Independent Decision Ownership
  • “Drove high-risk change initiatives in complex calculation and workflow areas by leveraging AI-assisted evaluation of solution options, surfacing trade-offs, and protecting downstream system integrity.” · Independent Decision Ownership
  • “Served as the primary decision interface between European business stakeholders, compliance teams, engineering, QA, and integration teams.” · Independent Decision Ownership
  • “Enabled delivery of regulatory and business-critical changes in complex calculation areas without compromising platform stability.” · Problem -> Change -> Business/Operational Result
  • “Reduced downstream delivery risk and rework by introducing AI-augmented structured discovery and solution evaluation practices.” · Problem -> Change -> Business/Operational Result
  • “Owned prioritization and roadmap inputs, balancing business value, regulatory risk, system stability, and delivery constraints across releases.” · Evidence-Led Prioritisation and Reversal
  • “Led product discovery and decision-making through stakeholder workshops, CAB forums, AI-assisted impact analysis, and cross-functional alignment across business, compliance, and technology teams.” · Evidence-Led Prioritisation and Reversal
  • “Built and mentored global BA teams, improving delivery maturity, stakeholder confidence, and execution quality across geographies.” · Creates Systems Others Run
  • “Reduced downstream delivery risk and rework by introducing AI-augmented structured discovery and solution evaluation practices.” · Creates Systems Others Run
  • “Contributed to enterprise-scale delivery governance by strengthening requirement clarity, traceability, and defect containment practices.” · Creates Systems Others Run
  • “Known for resolving stakeholder conflict, aligning initiatives to business objectives, and balancing speed, risk, and long-term value.” · Multi-Party Resolution Under Pressure
  • “Served as the primary decision interface between European business stakeholders, compliance teams, engineering, QA, and integration teams.” · Multi-Party Resolution Under Pressure
Outcomes stated in the CV
  • Enabled delivery of regulatory and business-critical changes in complex calculation areas without compromising platform stability.
  • Improved stakeholder alignment and trust across EU business teams through transparent, trade-off driven decision-making.
  • Reduced downstream delivery risk and rework by introducing AI-augmented structured discovery and solution evaluation practices.
  • Received EITSI Peer Recognition (2021).
  • Awarded Star Performer (2020).
Anonymised CV (exactly what the AI saw)
PROFESSIONAL SYNOPSIS
Product and Delivery Leader with 17 years of experience driving business outcomes in
complex, high-risk enterprise systems. Proven track record of owning ambiguous
problems, leading cross-functional and multi-region stakeholders, and delivering scalable
solutions through clear trade-offs and pragmatic decision-making. Known for resolving
stakeholder conflict, aligning initiatives to business objectives, and balancing speed, risk,
and long-term value. Increasingly leveraging AI-assisted discovery, impact analysis,
documentation structuring, and decision support to improve product velocity and
delivery precision in regulated environments.
WORK EXPERIENCE
Eurofins IT Solutions (April 2014 – August 2025)
Product & Delivery Leader (Senior Product / Program Management responsibilities)
Eurofins IT Solutions supports global laboratory and regulated scientific systems across
Food, Pharma, Environment, and Clinical domains. Eurofins IT Solutions India (EITSI)
exclusively caters to Eurofins Global IT business needs, providing world-class, high-quality
IT Solutions and Services with a special focus on next generation Laboratory Information
Management System (LIMS) in addition to creating and delivering various internal
applications and IT products for the Eurofins Group.
Program/Project: Eurofins – eLIMS-NG – CL-AP
Project Duration: April 2014 – August 2025
Client: Eurofins IT Solutions, India
Domain: Life Sciences, Laboratory Services, Clinical Services
Role: Product & Delivery Leader
Scope: Global platform | Multi-country EU stakeholders | Cross-functional teams |
Compliance-critical domain
Key Accountabilities & Impact:
➢ Accountable for product ownership and business leadership of eLIMS-NG, a global
laboratory information platform supporting regulated scientific workflows across
multiple regions.
➢ Owned prioritization and roadmap inputs, balancing business value, regulatory
risk, system stability, and delivery constraints across releases.
➢ Led product discovery and decision-making through stakeholder workshops, CAB
forums, AI-assisted impact analysis, and cross-functional alignment across
business, compliance, and technology teams.
➢ Drove high-risk change initiatives in complex calculation and workflow areas by
leveraging AI-assisted evaluation of solution options, surfacing trade-offs, and
protecting downstream system integrity.
➢ Served as the primary decision interface between European business
stakeholders, compliance teams, engineering, QA, and integration teams.
➢ Built and mentored global BA teams, improving delivery maturity, stakeholder
confidence, and execution quality across geographies.
Selected Outcomes & Business Impact:
• Enabled delivery of regulatory and business-critical changes in complex calculation
areas without compromising platform stability.
• Improved stakeholder alignment and trust across EU business teams through
transparent, trade-off driven decision-making.
• Reduced downstream delivery risk and rework by introducing AI-augmented
structured discovery and solution evaluation practices.
Product Strategy | Program Leadership | Enterprise Platforms | AI-
Augmented Delivery | Stakeholder Alignment | Regulated Systems
Bangalore, Karnataka
Availability: Open to Product / Program /
Leadership roles
CORE COMPENTENCIES
✓ Product Strategy, Discovery &
Roadmapping
✓ Business & Stakeholder Leadership (Multi-
Region)
✓ Complex Systems & Risk-Aware Decision
Making
✓ Program & Cross-Team Delivery Leadership
✓ Regulatory & Compliance-Critical Platforms
✓ ServiceNow CSM & ITSM (Functional
Leadership)
✓ Agile & AI-Augmented Product Delivery
✓ AI-Assisted Discovery, Risk Analysis &
Documentation Acceleration
Enterprise Platforms & Delivery Tooling
(Leadership Exposure)
✓ ServiceNow, SQL
✓ Modelling tools (Visio, Bizagi)
✓ ALM tools (Azure Devops, Jira)
AI & Automation Exposure
✓ Generative AI tools for requirement
drafting, documentation structuring, and
risk surfacing
✓ AI-supported impact analysis in complex
enterprise platforms
✓ Exploration of workflow automation
opportunities in regulated systems
[CANDIDATE] SENArnav [CANDIDATE]
[EMAIL REDACTED]
+91 99014 783029901478302
[CANDIDATE]-senlinkedin.com/in/[CANDIDATE]-[CANDIDATE]
ACHIEVEMENTS
✓ EITSI Peer Recognition – 2021
✓ Star Performer – 2020
EDUCATION CREDENTIALS
B.Tech. in Electronics and Telecommunication
Dr. B.A. Tech. University, July 2005, First Class
with Distinction- 70%
EARLIER EXPERIENCE
Mphasis Pvt. Ltd. (Aug 2008 – Mar 2014)
QA Engineer
Mphasis Limited is an IT services and consulting company that provides infrastructure
technology and applications outsourcing services. It serves financial services, telecom,
logistics, and technology industries.
➢ Enterprise testing across Banking, Logistics, Financial Services
➢ Exposure to large-scale, multi-client delivery environments
➢ End-to-end manual and functional testing across web and enterprise applications,
including requirements analysis, test planning, test case design, execution, and
defect reporting
➢ Hands-on experience in UAT support, working closely with business stakeholders to
validate critical workflows and ensure release readiness
➢ Defect management using tools like JIRA, including root cause analysis, severity
prioritization, and retest cycles
➢ Collaboration with cross-functional teams (BA, developers, product owners) in
Waterfall and Agile/Scrum delivery models
➢ Strong exposure to regression, integration, and system testing to ensure stability
across frequent releases
➢ Contributed to enterprise-scale delivery governance by strengthening requirement
clarity, traceability, and defect containment practices.
Redacted: name ×5, email ×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 (3)
  • 9/29/2026, 11:35:16 AMsystemanalysis completed{"PM_score":29,"SPM_score":36}
  • 9/29/2026, 11:35:16 AMsystemrole assigned best fit{"role":"SPM","PM_score":29,"SPM_score":36}
  • 9/29/2026, 11:29:26 AMsystemcv ingested{"file":"03_arnav_sen.pdf","role":"AUTO","redactions":{"name":5,"email":1},"name_detected":true}