Jobs Companies Prudential plc Business Intelligence Manager, Operations Analytics

Sobre esta vaga de Business Intelligence Manager, Operations Analytics na Prudential plc

Prudential plc · Presencial · Singapore

Prudential’s purpose is to be partners for every life and protectors for every future. Our purpose encourages everything we do by creating a culture in which diversity is celebrated and inclusion assured, for our people, customers, and partners. We provide a platform for our people to do their best work and make an impact to the business, and we support our people’s career ambitions. We pledge to make Prudential a place where you can Connect, Grow, and Succeed.

Job Profile Summary

We’re seeking a strategic and hands-on Operations Analytics Manager to uncover actionable insights across our operations value chain. This role is ideal for someone who thrives at the intersection of data science, operational strategy, and business transformation—someone who can frame the right problem, explore the data landscape, and drive decisions that matter.

Key Responsibilities

  • Frame the problem: Translate business pain points into structured problem statements using issue trees

  • Explore the data: Conduct exploratory data analysis (EDA) to identify root causes, patterns, and anomalies across operational processes

  • Hypothesis-driven analytics: Formulate and test hypotheses using statistical and scripting methods to validate root causes and solution levers

  • Insight generation: Translate complex data into clear, actionable insights for senior stakeholders across underwriting, claims, and operations

  • Action design: Recommend and track interventions based on data-driven findings

  • Data handling: Use SQL and Python to extract, clean, and join datasets from multiple sources into tidy, analysis-ready formats

  • Framework development: Build repeatable analytics frameworks and dashboards to monitor performance, quality, and risk signals

  • Partner cross-functionally: Collaborate with product, tech, and frontline teams to ensure insights are embedded into decision-making and design

Qualifications & Skills

  • 5+ years in data analytics, operations strategy, or consulting (insurance or financial services preferred)

  • Strong command of SQL and Python for data extraction, transformation, and analysis

  • Experience with EDA, hypothesis testing, and root cause analysis

  • Familiarity with issue tree frameworks 

  • Ability to translate data into business impact—clear communicator with executive presence

  • Experience working with large, messy, or cross-functional datasets

  • Exposure to insurance operations, claims workflows, or underwriting systems

 

Prudential is an equal opportunity employer. We provide equality of opportunity of benefits for all who apply and who perform work for our organisation irrespective of sex, race, age, ethnic origin, educational, social and cultural background, marital status, pregnancy and maternity, religion or belief, disability or part-time / fixed-term work, or any other status protected by applicable law. We encourage the same standards from our recruitment and third-party suppliers taking into account the context of grade, job and location. We also allow for reasonable adjustments to support people with individual physical or mental health requirements.

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Sobre a Prudential plc

We are Prudential. For every life, we are partners. For every future, we are protectors. Prudential plc provides life and health insurance and asset management to 17 million customers across 20 markets in Asia and Africa. We are headquartered in Hong Kong and have dual primary listings on the Stock Exchange of Hong Kong and the London Stock Exchange. We are focused on four strategic regions: Greater China, ASEAN, India and Africa. Our customers are served by around 55,000 agents and more than 200 bank partners. Prudential plc is not affiliated in any manner with Prudential Financial, Inc., a company whose principal place of business is in the United States of America or with the Prudential A

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