Pooja Srivastava

About Pooja Srivastava

AI Product & Solutions Leader with 20+ years of experience building and scaling enterprise solutions across advanced analytics, NLP, and GenAI (RAG)+ agentic workflows. I specialize in taking ambiguous problems from discovery → product strategy → solution architecture → production delivery → adoption, partnering across Data Science, Engineering, Architecture/Infra, Security/Legal, and GTM.At Wolters Kluwer, I’ve productionized multiple AI products and platform capabilities embedded into enterprise workflows and Salesforce—delivering measurable outcomes including ~95% routing accuracy and ~$2M+/year savings,~90% reduction in manual effort unlocking $1.5M+ annual advisory capacity, and ~60% faster query resolution through GenAI search and retrieval experiences. I’ve also led large-scale validation and data integrity initiatives and supported commercialization by enabling client discovery, demos, and repeatable sales/implementation playbooks. My strengths are practical and enterprise-focused: designing workflows, taxonomies, and solution architectures, defining API/integration strategies, and building evaluation scorecards, telemetry, and guardrails that make AI reliable in real-world environments. I’m equally comfortable in client-facing settings: leading workshops, translating requirements, handling stakeholder objections, and presenting to executives as I am driving cross-functional delivery and launch readiness. Core strengths: GenAI (RAG, agent orchestration, tool-use), ML & predictive analytics, NLP/information retrieval, taxonomy & knowledge modeling, enterprise architecture (APIs/integrations), evaluation & monitoring/telemetry, security-by-design (RBAC/auditability), cross-functional leadership, client engagement, and executive storytelling.

Experience

1. Senior Manager Data Science (Financial & Corporate Compliance)

   Wolters Kluwer

   Feb 2022 — Present · US

   Senior Manager, Data Science (AI Product Owner) — Wolters Kluwer | Feb 2022–Present- Lead AI product strategy and roadmap for enterprise compliance/advisory solutions; translate customer pain points into PRDs, prioritized backlogs, and measurable release outcomes across DS/Eng/Design, Legal/Compliance, Security, and GTM- Productionized multiple AI products end-to-end (discovery → architecture → launch → adoption), instrumenting activation/time-saved KPIs and running beta/feedback councils to iterate based on telemetry and customer outcomes- Product-managed Penny (agentic AI) for Salesforce case classification/routing; established success criteria and QA bars to achieve ~95% accuracy and ~$2M+ annual savings; partnered with GTM on pricing/positioning and sales playbooks- Shipped NILS AI Assist (GenAI search / RAG-style retrieval) for compliance document discovery; designed UX + guardrails to cut query resolution time by ~60%, improving analyst throughput and SLA performance; instrumented activation and time-saved metrics- Led Data Integrity AI for 1071/HMDA validations on a digital-twin architecture; defined field-level validation UX, traceability, and reporting—expanding annual revenue potential by $5M+ and accelerating compliance review cycles- Partnered with Architecture/Infra teams on enterprise integration and API strategy (capacity, orchestration, resilience) to deliver scalable, compliant releases across platform and Salesforce-embedded workflows- Instituted security-by-design and quality guardrails: RBAC, auditability, SOC2-aligned delivery processes, human-in-the-loop thresholds, plus release notes and rollback plans for regulated enterprise customers- Enabled GTM and customer adoption through executive demos, ROI narratives (capacity unlocked,$/case savings), and technical discovery workshops; used data-backed win/loss insights to refine roadmap and improve conversion/expansion.

Education

• Eastern University

  Master of Science - MS, Data Science

• Kumaun University

  Bachelor of Applied Science - BASc, Mathematics

  1999 — 2001

• IMS UNISON UNIVERSITY

  Master of Computer Applications - MCA, Computer Science

  2002 — 2005