Candidate Evaluation Scoring Report: Fractional Technical Project Manager, Enterprise Healthcare Software Implementation

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Candidate Evaluation Scoring Report: Fractional Technical Project Manager, Enterprise Healthcare Software Implementation

Fractional India-based technical PM role supporting Phase 1 of an enterprise healthcare-oriented SaaS implementation for US stakeholders, with ownership of sprint execution, RAID/dependency tracking, executive reporting, UAT, QA coordination, data migration readiness, training coordination, and AI-assisted distributed delivery governance.

Scoring Notes
Scores are based only on the submitted evaluation response, JD, and project context.
Missing or generic evidence was scored conservatively, especially for healthcare, HIPAA-adjacent, cloud/API, data migration, and hands-on artifact proof.
AI assistance or AI familiarity was not treated as disqualifying; generic or polished answers are used as prompts for ownership and practical-depth probes.

Scoring Parameters
- Enterprise technical delivery and senior ownership (20): Depth of experience managing complex enterprise software delivery, team coordination, technical dependencies, and senior PM ownership.
- US stakeholder and executive communication (15): Evidence of direct work with US stakeholders, structured meetings, escalation handling, written follow-up, and executive-ready communication.
- Execution artifacts and governance discipline (20): Ownership of WBS, sprint plans, milestone trackers, RAID logs, decision logs, action trackers, UAT trackers, and status reporting.
- Healthcare, SaaS, technical risk, and regulated-domain fit (20): Evidence of healthcare/HIPAA-adjacent, sensitive data, APIs, cloud deployment, security/privacy, data migration, auditability, and operational risk awareness.
- Agile, QA, UAT, and change-control mechanics (15): Ability to manage sprint planning/reviews, acceptance criteria, QA/UAT readiness, defect triage, scope-change separation, and signoff workflows.
- Distributed fractional delivery, AI-assisted governance, and availability (10): Fit for 10-hour weekly fractional execution, India-US overlap, coordination of vendors/fractional specialists, and quality controls for AI-assisted delivery.

Candidate Ranking
- Rajeev Raghu Raman Arunachalam: 70/100 - Possible shortlist

Rajeev Raghu Raman Arunachalam
Strong general enterprise PM, Agile governance, PMO, artifact, RAID, UAT, and executive reporting evidence. Fit is weakened by limited direct healthcare implementation evidence, limited concrete SaaS/API/cloud/data migration examples, and mostly generic descriptions rather than redacted artifacts or specific delivery outcomes.
Enterprise technical delivery and senior ownership: 7/10 - Describes multi-year enterprise BFSI Agile delivery, PM/Scrum Master work, PMO governance, cross-functional teams, QA, vendors, dashboards, and a 36+ member service delivery context, but examples are high-level and not deeply technical.
US stakeholder and executive communication: 7/10 - States experience with US/global consulting stakeholders, executive-ready reporting, dashboards, action follow-up, time-zone overlap, and structured written summaries; however, specific decisions, escalations, or founder/executive examples are limited.
Execution artifacts and governance discipline: 8/10 - Provides a strong list of personally maintained artifacts including sprint plan, milestone tracker, RAID log, decision log, client action tracker, UAT tracker, bug/change tracker, status report, and resource plan, with practical descriptions of use.
Healthcare, SaaS, technical risk, and regulated-domain fit: 5/10 - Shows awareness of PHI/PII, role-based access, audit trails, encryption, security review, data migration validation, test data, UAT ownership, and training readiness, but healthcare experience appears limited to certification/basic concepts and analogous BFSI sensitive-data experience.
Agile, QA, UAT, and change-control mechanics: 7/10 - Explains sprint planning, acceptance criteria, QA/UAT linkage, sprint review, defect/change classification, impact assessment, decision logging, retesting, and signoff workflow. Evidence is relevant but mostly process-level rather than tied to a specific completed project.
Distributed fractional delivery, AI-assisted governance, and availability: 7/10 - Confirms approximately 10 hours per week, India-based US overlap, immediate/early start, distributed team coordination, and sensible AI quality controls. AI-assisted delivery experience is mostly documentation/planning/checklist use rather than managing AI development agents.
Strong points:
- Strong PM artifact vocabulary and clear understanding of RAID, decision logs, action trackers, UAT trackers, executive status reports, and sprint governance.
- Relevant enterprise delivery background in regulated/sensitive BFSI and consulting PMO environments.
- Good structured approach to delayed architecture review, UAT triage, risk communication, and stakeholder follow-up.
- Availability appears aligned with the fractional 10-hour India-US overlap model.
Weak points:
- No direct healthcare software implementation, claims/data interchange, or HIPAA-adjacent project example was provided.
- Limited concrete evidence of managing APIs, AWS/cloud deployment, architecture review, security/privacy review, or data migration beyond checklist-level awareness.
- Submitted examples are polished and broad but light on specific outcomes, artifacts, dates, metrics, or personally owned decisions.
- Executive status report was described as a template rather than shown as a redacted sample.
Probe further:
- Ask the candidate to walk through one specific enterprise project end to end: team size, sprint cadence, artifacts personally maintained, major risks, decisions driven, and final outcome.
- Ask for a live explanation of a RAID log or weekly status report structure, including how risks were escalated and closed.
- Probe healthcare readiness: how would he handle PHI/PII, audit logging, role-based access, test data, migration validation, and UAT signoff for this PPRS Phase 1 context?
- Ask him to draft or outline a 1-page executive weekly status report live from a short scenario with architecture, QA, UAT, and client-decision risks.
- Clarify actual AI-assisted delivery ownership: has he managed developers using AI code-generation tools, and what review gates, test coverage, and security checks did he enforce?