Aditya Birla Sun Life Insurance
Sub VH - Analytics
Skills
1 month ago
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Important information
Contract type:
Permanent
Location:
Maharashtra, India
Work mode:
Onsite
Published on:
8 September 2026
What they need
ey Responsibilities
- Define and execute enterprise analytics and data strategy aligned with business objectives.
- Build a data-driven culture across Sales, Distribution, Operations, Claims, Underwriting, Customer Experience, Finance, and HR.
- Lead AI, machine learning, predictive analytics, and GenAI initiatives.
- Establish enterprise data governance, quality, and management frameworks.
- Act as a strategic advisor to executive leadership.
- Build and lead a high-performing Analytics & Data Science Center of Excellence.
- Partner with the CTO to shape technology and data platforms.
- Drive measurable business outcomes through analytics-led interventions.
Desired Outcomes
- Enterprise-wide adoption of analytics and AI.
- Improved customer retention and persistency.
- Enhanced sales productivity and channel effectiveness.
- Reduced operating costs through automation and process optimization.
- Strong data governance and a single source of truth for reporting.
Qualifications Bachelor’s degree in Engineering , Mathematics, Statistics, Computer Science, or related field . MBA or Master’s degree preferred.
Experience 15–20+ years in Analytics, Data Science, Business Intelligence, Data Management, or Digital Transformation, with at least 8 years in senior leadership roles. Prior Insurance/BFSI experience preferred.
Technical Expertise
Enterprise Data Strategy, AI/ML, Generative AI, Predictive Modeling, Cloud Analytics Platforms, Data Governance, Data Lakes, Power BI/Tableau, SQL, Python, R, MLOps , and Customer Analytics.
Leadership Competencies
Strategic Thinking, Executive Presence, Business Partnership, Change Leadership, Innovation Mindset, Stakeholder Management, Talent Development, and Program Leadership.
Success Metrics
Business value delivered through analytics, adoption of AI initiatives, KPI improvements, data governance maturity, user adoption of analytics platforms, and analytics ROI.
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