Data Analytics Senior Specialist (Chuyên Viên Phân Tích Dữ Liệu)

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.

1. BAU Reporting & Analytics

·    Own and manage BAU reporting and dashboard activities for assigned business functions, ensuring accuracy, consistency, reliability, and timely delivery.

·    Develop deep expertise in relevant business processes, data structures, data sources, and business rules, serving as a trusted analytics partner for business stakeholders.

·    Proactively identify opportunities to streamline, automate, and standardize reporting and data-processing activities.

·    Maintain robust data definitions, business rules, data dictionaries, calculation logic, and technical documentation to strengthen data governance and ensure knowledge continuity.

·    Continuously improve reporting and analytical solutions by adopting appropriate technologies, analytical techniques, and data visualization best practices.

·    Proactively monitor data quality and reporting processes, identify potential issues or risks, and drive appropriate corrective actions to ensure business continuity.

2. Project-Based Analytics & Business Intelligence

·    Partner with stakeholders to understand business objectives, challenges, and opportunities, translating business needs into clear analytical requirements and fit-for-purpose solutions.

·    Design and deliver dashboards, BI solutions, and deep-dive analyses that provide actionable insights and support data-driven decision-making.

·    Prepare and validate datasets to support advanced analytics, predictive modeling, and Machine Learning initiatives in collaboration with local and regional analytics teams.

·    Manage assigned analytics initiatives across the delivery lifecycle, from requirement clarification and data preparation through development, validation, UAT, implementation, and ongoing enhancement.

·    Ensure analytical solutions are scalable, maintainable, well-documented, and aligned with established data and reporting standards.

3. Business Partnership & Stakeholder Management

·    Build strong working relationships with business stakeholders and act as a trusted analytics partner for assigned functions.

·    Translate business questions and operational challenges into measurable analytical problems, KPIs, and data-driven solutions.

·    Provide analytical perspectives and recommendations to support business performance monitoring, operational improvement, and management decision-making.

·    Communicate analytical findings effectively to technical and non-technical stakeholders, transforming complex data into clear, concise, and actionable insights.

·    Proactively challenge unclear or inefficient reporting requirements and recommend more effective, scalable, and sustainable solutions.

4. Knowledge Sharing & Team Contribution

·    Promote knowledge sharing and contribute to building stronger business, data, analytics, and technical capabilities across the team.

·    Ensure appropriate documentation, backup, and knowledge transfer for critical analytics processes and reporting solutions.

·    Coach and support junior team members when needed, sharing best practices in data processing, analytics, visualization, and problem-solving.

·    Act as a Subject Matter Expert (SME) in assigned business and data domains and contribute to the standardization of analytics practices.

·    Contribute to broader team priorities, transformation initiatives, and other assignments as required by management.

Job Requirements

Education & Experience

·    Bachelor's degree or above in Data Analytics, Business Analytics, Statistics, Mathematics, Computer Science, Information Systems, Engineering, Economics, Finance, or a related discipline.

·    Typically 4–6 years of relevant experience in Data Analytics, Business Intelligence, Data Management, Reporting, or a related field.

·    Demonstrated experience working with business stakeholders and independently delivering reports, dashboards, analytical solutions, or data-driven initiatives.

·    Experience in insurance, financial services, banking, or another data-intensive industry is an advantage.

Technical & Analytical Capabilities

·    Strong hands-on experience with Power BI or equivalent Business Intelligence platforms, including dashboard development, semantic/data modeling, visualization, and performance optimization.

·    Strong proficiency in SQL, with the ability to independently extract, transform, reconcile, and analyze large and complex datasets.

·    Good understanding of data modeling, ETL/ELT processes, data quality controls, data validation, and reconciliation principles.

·    Experience with modern data platforms such as Data Lake, Data Warehouse, Databricks, or cloud-based analytics environments is highly desirable.

·    Strong proficiency in Excel and practical experience with analytical and reporting automation tools.

·    Experience with Python, R, Power Automate, or similar analytics and automation technologies is an advantage.

·    Ability to develop well-structured data models, KPIs, business rules, and reusable analytical solutions.

·    Strong analytical and problem-solving skills, with the ability to identify patterns, investigate root causes, and translate data into actionable business insights.

Business & Stakeholder Capabilities

·    Strong business acumen with the ability to understand business processes, operational challenges, and key performance drivers.

·    Ability to translate business requirements into data requirements, analytical approaches, KPIs, dashboards, and actionable recommendations.

·    Strong stakeholder management and communication skills, with the ability to work effectively across business, technology, data, and analytics teams.

·    Ability to present complex analytical findings in a clear, concise, and business-oriented manner.

·    Demonstrated ability to manage multiple priorities and deliver high-quality outputs within agreed timelines.

Data Governance & Quality Mindset

·    Strong understanding of data quality, data integrity, data lineage, data definitions, and documentation principles.

·    Maintain appropriate controls and validation processes to ensure analytical outputs are accurate, traceable, and reliable.

·    Demonstrate appropriate awareness of data privacy, confidentiality, security, and governance requirements, particularly when working with sensitive customer and business information.

·    Promote standardized business definitions and single-source-of-truth principles across reporting and analytical solutions.

 

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.