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Straive

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Engagement Manager Consultant

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Summary

Director-level analytics consulting leader to head Straive's insurance practice in India, advising C-suite clients on data/AI roadmaps, owning the consulting unit's P&L and RFPs, and driving GenAI/LLM deployments plus predictive modelling (UBI, fraud, catastrophe risk) for global insurance clients. Based in Pune, Bengaluru, or Delhi/NCR.

As we navigate 2026, the insurance landscape has shifted from "Detect and Repair" to "Predict and Prevent." We are seeking a visionary Director of Analytics Consulting to lead our insurance practice in India. This is a high-impact leadership role where you will bridge the gap between complex data science and C-suite insurance strategy. You will drive the adoption of Generative AI (GenAI), Autonomous Underwriting, and Real-time Risk Assessment for our global insurance clients, ensuring data becomes a competitive moat, not just an asset.


Key Responsibilities


1. Strategic Leadership & Client Advisory


• Trusted Advisor: Serve as the primary strategic consultant for C-suite stakeholders to define their 3-5 year data and AI roadmaps.

• Industry Thought Leadership: Publish whitepapers and lead webinars on 2026 trends, such as Hyper-personalization, Ethical AI Governance, and IoT-driven "Connected Insurance."

• Value Realization: Shift clients focus from "model accuracy" to "business outcomes" (e.g., improving Combined Ratio, reducing Churn, or optimizing Customer Lifetime Value).


2. Practice Growth & Business Development • P&L Management: Own the revenue and margin targets for the Insurance Analytics consulting unit.

• Proposal Excellence: Lead large-scale RFP responses, designing complex analytical solutions that integrate with legacy core systems (e.g., Guidewire, Duck Creek).

• Market Expansion: Identify opportunities to cross-sell advanced analytics services into existing audit or strategy accounts.


3. Delivery Excellence & AI Innovation • GenAI Integration: Oversee the deployment of LLM-based agents for automated claims processing and "Co-pilot" tools for underwriters. • Predictive Modelling: Lead teams in developing sophisticated models for usage-based insurance (UBI), fraud detection (using graph analytics), and catastrophic risk modelling. • Digital Ethics: Ensure all consulting engagements adhere to the latest AI regulatory frameworks (e.g., EU AI Act, local transparency mandates).


4. People & Talent Development • Team Building: Mentor a multi-disciplinary team of Data Scientists, Analysts, and Data Engineers. • Culture: Foster a "consultant-first" mindset where technical staff are trained in storytelling, visualization, and insurance business logic.


Skills

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