Prabhat Mishra

• 12.5-year Life Sciences career culminates here — Authored Lilly’s end-to-end DE, ML, and AI strategy; multi-year roadmap ownership, VP/SVP alignment, full ecosystem delivery from greenfield to production.
• Built cloud-native Data & Analytics platform from zero — AWS medallion architecture, 20+ sources, >200TB; no inherited systems, no existing team; foundation for all ML and AI at scale.
• Leader of leaders — Built and led engineering squads across DE, MLOps, and AI; squad leads and tech leads reporting directly; promoted 8 to senior/lead roles in 3 years through structured coaching and stretch assignments.
• Advanced MLOps from greenfield to Level 3 — Automated CI/CD deployments, continuous model monitoring, experiment tracking, and model governance across 20+ production models; roadmap to Level 4 in active execution.
• Delivered pharma’s first C-suite Agentic AI product — Real-time patient analytics consumed by executive leadership; presented to VP/SVP; scaling to Level 2 multi-agent architecture across additional data sources.
• Operationalised 20+ production models — Marketing Mix Modelling, Multi-Touch Attribution, Audience Segmentation, Dynamic Targeting; 50% faster time-to-market, 70% fewer manual touchpoints, 10,000+ hours saved annually.
• Built HIPAA/GDPR-compliant data pipelines — 75%+ workflow automation, 50GB+ weekly throughput; full regulatory auditability across pharma commercial and clinical domains.
• Established GenAI and LLM framework — Responsible AI governance, prompt standards, cost controls, enterprise guardrails; organisation’s first mover on Agentic AI, real-time ML, and cloud-native DE.
• Reduced engineering dependency by 40% — Modular data and AI primitives (feature stores, model registries, inference APIs) enabling Analytics, Data Science, and Marketing to self-serve.
• $5M+ operational efficiency — Cloud cost optimisation, process automation, vendor renegotiation, and platform consolidation.

Key Impact

• $100M+ incremental revenue via AI-powered targeting and personalisation.
• $10M+ marketing effectiveness gains from real-time ML personalisation.
• $5M+ operational savings through automation and cloud optimisation.
• 8 promotions in 3 years — senior/lead talent pipeline built from within.
• Lilly’s first Agentic AI — C-suite-consumed patient analytics, scaling to enterprise multi-agent platform.

• Designed AWS Data Lake platform for a major banking client — End-to-end analytics and visualisation at enterprise scale.
• Designed and implemented scalable data pipelines for high-volume data processing.
• Mentored junior engineers on best practices in data architecture and coding standards.
• Collaborated with stakeholders to identify data requirements and translate them into technical specifications.

• Primary client Pfizer (5.9 years) and Merck — Based in Accenture’s Argentina office for 3 years; led project delivery and cross-geography stakeholder management for Pfizer’s commercial analytics and data engineering function.
• Led end-to-end project delivery for Pfizer — Commercial analytics, clinical/R&D data pipelines, and self-service ingestion platform; stakeholder management across Latin America and global Pfizer teams.
• Built Self-Service Ingestion Platform — Large-scale clinical research data into Data Lake and Warehouse; enabled advanced analytics and self-service for pharma commercial and research teams.
• Led SAP Global Data Hub implementation — Cross-functional team delivery; data sourcing and warehousing for Managed Market Domain in Commercial Analytics.
• Drove process automation — Measurable operational savings across data engineering workflows for Pfizer and Merck.
• Delivered exceptional results under tight deadlines, consistently prioritizing tasks effectively to meet project timelines without compromising quality or accuracy.
• Contributed significantly towards setting up an automated monitoring mechanism using state-of-the-art technologies and tools, which led to proactive issue identification and resolution.