AVP/VP Practice Lead – Data & Analytics

 

 

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 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.

• Define measurable outcomes and quantified value cases tied to expense ratio, loss ratio, speed-to-market,

and data quality uplift.

 

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.

• Own the full solution lifecycle — from problem framing and use-case selection through architecture,

deployment, and realized business value.

• Drive RFPs, proposals, and client demonstrations for data, analytics, and reporting opportunities,

articulating business value and operating models with clarity.

• Ensure every solution is resilient, scalable, secure, and aligned with both client objectives and enterprise

architecture standards.

 

 

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.

• Work alongside business units and CoEs to embed analytics and AI directly into operational workflows —

underwriting workbenches, claims systems, and portals.

• Support joint opportunity validation, solution scoping, and go-to-market planning in close coordination with

sales and account leadership.

 

 

5. Innovation & Continuous Improvement

• Champion innovation through automation, AI/ML, and advanced analytics — including propensity modeling,

fraud detection, segmentation, and pricing support.

• Build and evangelize reusable assets, accelerators, data models, dashboards, and playbooks that reflect

Xceedance's data & analytics offerings.

• Continuously refine solutioning methodologies, delivery toolkits, and stakeholder engagement practices to

elevate speed, consistency, and business impact.

 

 

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.