Practice Lead; AVP​/VP –Data & Advanced Analytics; Solutioning, Predictive Analytics, P&C Insurance

Position: Practice Lead(AVP/VP) –Data & Advanced Analytics (Solutioning, Predictive Analytics, P&C Insurance)
Location: Bengaluru

A Reputed IT MNC is hiring for :
Practice Lead (AVP/VP Level) – Data & Advanced Analytics.

Key Skills :
Insurance (P&C) + Data & Analytics+ Solutions
Experience : 12-15+ years
Practice Lead – Data & Advanced Analytics

Location:

India (Gurgaon, Noida, Pune, Bengaluru, Kolkatta)

Role Overview
A senior leadership role accountable for shaping, architecting, and delivering customer-centric data and advanced analytics solutions for insurers, reinsurers, MGAs, and brokers. The position owns end-to-end solution strategy across data platforms, BI/MI, advanced analytics, and AI/ML; sponsors enterprise transformation programs; and collaborates across functions to translate client priorities into scalable,
industrialized offerings.

Key Skills &

Competencies:

Domain & Functional

• Deep grasp of the P&C insurance value chain — underwriting, pricing, claims, finance, and distribution —
and the associated data/analytics use cases.

• Demonstrated ability to translate complex business and risk problems into practical, scalable data and
analytics solutions.
Technical & Architectural

• Strong command of modern data engineering and analytics stacks, including cloud data platforms,
ETL/ELT, data quality, MDM, and reporting tools.

• Hands-on experience applying advanced analytics and AI/ML in insurance — predictive modeling, NLP, risk scoring, and intelligent automation.

• Working knowledge of APIs, integration patterns, and cloud architectures that underpin data-driven
solutions.
Solutioning & Consulting

• Proven track record in solution architecture, proposal development, and RFP management for data and
analytics engagements.

• Compelling storytelling and executive communication skills that connect data initiatives to P&L and balance sheet outcomes.
Collaboration & Leadership

• Strong stakeholder management and influencing capabilities across business, actuarial, IT, and operations.

• Demonstrated ability to lead virtual, cross-functional global teams and to mentor SMEs and data
professionals.

Qualifications & Experience

• Bachelor's or Master's degree in Engineering, Computer Science, Analytics, Statistics, Business, or a
related discipline.

• 15+ years of experience in data, analytics, or technology-led transformation roles within insurance or
financial services.

• 7+ years of experience leading data platform, BI/MI, or advanced analytics initiatives for global clients.
Proven success in client-facing roles and in shaping and delivering large-scale data & analytics transformation programs.

Key Responsibilities

1. Transformation & Strategic Consulting

• Advise clients on holistic data & analytics transformation roadmaps spanning data foundations, self-service MI, predictive analytics, and AI-enabled operations.

• Identify, shape, and prioritize high-impact use cases across underwriting, pricing, claims, finance, and
distribution — including underwriting workbench insights, loss-cost modeling, claims triage, and producer
analytics.

2. Client Engagement and Solution Strengthening

• Lead the design and deployment of end-to-end data and analytics solutions, covering data platforms, MI/BI, advanced analytics, and AI/ML.

• Serve as a business architect, partnering with clients to envision and deliver outcomes powered by agentic AI offerings.

• Drive RFPs, proposals, and client demonstrations for data, analytics, and reporting opportunities,
articulating business value and operating models with clarity.

3. Techno-Functional & Domain Leadership

• Act as a subject matter expert at the intersection of P&C insurance and data/analytics.

• Bridge actuarial, underwriting, claims, and technology teams on solution feasibility, data requirements, and implementation pathways.

• Maintain fluency in modern data stacks, cloud platforms, AI/ML techniques, and the broader insurtech
ecosystem to continually sharpen the practice's offerings.

4. Cross-Functional Collaboration

• Partner with delivery, process excellence, digital platform, and technology teams to architect and deliver
integrated data solutions.

• Engage digital and platform teams on architecture, integration patterns, and deployment models such as
cloud data lakes, warehouses, and API-driven services.

5. Innovation & Continuous Improvement

• Champion innovation through automation, AI/ML, and advanced analytics — including propensity modeling, fraud detection, segmentation, and pricing support.