
Job Description:
Lead Reinsurance Data Analyst, Assurant, GCC-India
This role is responsible for executing and optimizing reinsurance operations with a strong focus on accuracy, controls, and efficiency. The Lead Reinsurance Data Analyst operates as an individual contributor.
The role evaluates data analyses, process optimization plans, business intelligence and AI-enabled tools to enhance operational effectiveness, improve cycle times, and strengthen controls. This position drives the modernization of processes and the scaling of operations through automation and emerging technologies.
Working Hours: 3 PM IST to 12 AM IST
This position will be in Bangalore, Hyderabad, Gurgaon & Chennai at our India location.
What will be my duties and responsibilities in this job?
1. Reinsurance Operations Execution & Oversight (40-50%):
- Lead core reinsurance settlement activities including client reporting and reconciliations
- Oversee and ensure data integrity across reinsurance systems and financial reporting outputs
- Ensure compliance with contractual terms, internal controls, and company policies
- Evaluate risks, discrepancies, and operational issues and recommend solutions
2. Data, Business Intelligence & AI Enablement (35-45%):
- Leverage data and business intelligence tools (e.g., Power BI, Alteryx, PowerQuery) to review trend/variance analyses and operational performance KPIs
- Utilize AI-enabled tools (e.g., Microsoft Copilot, ChatGPT, automation platforms) to review analyses of large volumes of data, data modeling
- Improve efficiency in reconciliations, reporting, and documentation
- Lead root-cause analysis and issue resolution
- Evaluate UAT for client integrations
- Review/approve process documentation for operational consistency
- Lead implementation of automation and tools of the future within reinsurance workflows
- Ensure outputs from systems, tools, and models are accurate, reliable, and well-controlled
3. Process Improvement & Operational Efficiency (20-25%):
- Evaluate/solution inefficiencies, manual processes, and control gaps within reinsurance operations
- Drive process redesign, standardization, and documentation efforts
- Lead or support initiatives focused on system integrations, automation, cycle time reduction, and scalability
- Foster a culture of continuous improvement, leveraging data to prioritize and measure impact
- Partner cross-functionally (Finance, Technology, Operations) to drive transformation efforts
What are the requirements needed for this position?
Education:
- Bachelors/Master's degree in accounting, Finance, Business, or related field
Experience:
- 3+ years of experience in finance/accounting
- Minimum 5+ years of experience in financial systems, data mapping, implementing automation solutions, business intelligence, working with digital transformation initiatives or tools of the future (e.g., AI tools, data platforms, workflow automation)
- 5+ years experience analyzing large volumes of data/data modeling
- Experience in monitoring and oversight of system outputs
- Aptitude for learning and applying AI-enabled tools to drive productivity and insight generation (Co-Pilot, ChatGPT, Claude)
Knowledge & Skills:
- Experience designing and implementing Alteryx workflows
- Advanced skills in data analytics and BI tools (Power BI, Power Query, or similar)
- Demonstrated ability to identify and implement process improvements and automation opportunities
- Strong analytical and problem-solving skills with attention to detail
- Ability to operate independently while influencing outcomes across teams and vendors
- Strong communication skills with ability to translate operational issues into business insights
- Control-minded with focus on accuracy, risk mitigation, and operational discipline
- Proven mindset focused on efficiency, continuous improvement, and innovation
What are the Preferred requirements needed for this position?
- Experience in Property & Casualty (P&C) insurance or reinsurance environment
- Strong understanding of reinsurance operations (premium, claims, settlements, reporting, reinsurance systems and data structures)
- Proven track record leading system implementations or enhancements
- Experience using AI-enabled tools to drive productivity and insight generation
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