Analytics Lead

Responsibilities:

• Lead MIS and analytics delivery: Own recurring management reporting, dashboards, ad hoc analysis, and decision-support products; ensure outputs are accurate, timely, consistent, and decision-oriented.
• Manage the end-to-end data lifecycle: Translate business requirements into data ingestion, transformation, modeling, validation, visualization, and production-support solutions.
• Lead and develop the team: Set priorities, allocate work, coach analysts and engineers, review technical outputs, remove delivery blockers, and build a collaborative, customer-centric and accountable team culture.
• Partner with senior stakeholders: Work closely with Department and Division Heads to clarify business questions, define success measures, challenge assumptions constructively, and communicate findings in clear business language.
• Drive process improvement and transformation: Identify how data analytics can simplify or improve manual, fragmented, or control-intensive processes and deliver measurable improvements in turnaround time, quality, cost, control, or customer outcomes.
• Strengthen data governance: Support in establishing clear metric definitions, data ownership, documentation, lineage, access management, and data quality issue-resolution processes.
• Build scalable data products: Develop reusable datasets and semantic models rather than one-off reports, with appropriate testing, version control, deployment discipline, and performance monitoring.
• Support insurance performance management: Enable analysis across relevant areas such as sales, distribution productivity, operations, and customer proposition.
• Explore emerging capabilities: Where relevant, assess and deliver practical AI use cases involving large language models and AI agents, with appropriate controls for data privacy, accuracy, security, and human oversight.

Qualifications:

• Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Economics, or related fields.
• 5-10 years of experience in Data Analytics, Business Intelligence, MIS, Data Engineering, or related areas, including team leadership.
• Strong expertise in SQL, Python/R, Power BI, ETL/ELT, data modeling, cloud data platforms, and data governance.
• Proven track record in delivering data-driven business improvements and transformation initiatives.
• Strong stakeholder management, communication, and presentation skills, with the ability to translate complex data into business insights.
• Experience in insurance or financial services is preferred.
• Hands-on leader with strong analytical, problem-solving, and decision-making capabilities.
• Collaborative, results-oriented, and able to manage multiple priorities while driving continuous improvement and change.
• Exposure to AI/LLM solutions, modern data architecture, and responsible AI practices is an advantage.