Senior Data Analyst

The Great Eastern Life Assurance Company Limited; Singapore; On-site; SGD 70,000 - 90,000; Full time

Job summary

A leading insurance company in Singapore is seeking a Senior Data Analyst to enhance audit processes through data analytics and AI. This role involves delivering enterprise-wide analytics initiatives and collaborating with stakeholders to develop scalable solutions. Candidates should have a Bachelor’s degree in a relevant field and at least 5 years of experience in business intelligence, focusing on data visualization and SQL programming. Strong communication skills and the ability to derive insights from complex datasets are essential.

Qualifications

• 5+ years of experience in business intelligence and analytics projects.
• Expertise in data visualization tools like Tableau, PowerBI, or Qlikview.
• Proficient in SQL programming and standard MS Office applications.
• Hands-on experience with big data tools such as Spark and Hadoop.
• Knowledge of statistical techniques and machine learning methods.

Responsibilities

• Design and enhance analytics assets for decision-making.
• Conduct deep dive analytics to identify risks.
• Maintain and optimize data models for integrity.
• Collaborate with stakeholders for aligned metrics logic.
• Manage the lifecycle of analytics models and data pipelines.
• Ensure compliance with policies and regulations.

Skills

Data visualization

SQL programming

Creating compelling narratives from data

Requirement gathering

Statistical analysis

Project management

Communication skills

Creativity

Education

Bachelor of Science degree in Business Analytics or equivalent

Tools

Tableau

PowerBI

Qlikview

SQL

Spark

Hadoop

scikit-learn

TensorFlow

Job description

The Senior Data Analyst plays a critical role in enabling Group Internal Audit to transform audit processes using data analytics and AI. This role is responsible for the successful delivery of enterprise-wide analytics initiatives, including deep dive analyses and end-to-end model lifecycle management. The analyst will independently lead projects, collaborate closely with key stakeholders, and apply advanced technical skills to implement scalable analytics solutions that drive audit coverage, productivity, and strategic decision-making.

• Design, build, and enhance visual analytics assets that support audit decision-making and risk identification.
• Conduct deep dive analytics to uncover patterns, anomalies, and emerging risks across complex datasets.
• Map out the analytics and AI roadmap for audit function.
• Maintain and optimise data models to ensure accuracy, integrity, and relevance.
• Collaborate with business stakeholders to align metrics logic with evolving business definitions.
• Collaborate with data scientists to manage the end-to-end lifecycle of analytics models, including data sourcing, development, validation, deployment, monitoring, and continuous improvement.
• Work closely with data engineers to define and build robust data pipelines and business data stores that support scalable analytics.
• Ensure all analytics initiatives comply with internal and external policies, guidelines, and regulations.
• Respond to ad-hoc data insight requests and support audit teams with timely, actionable intelligence.
• Proactively share best practices in risk management and analytics innovation.

• Bachelor of Science degree in Business Analytics, Statistics, Economics, Actuarial Science, Data Science, Computer Science, Mathematics or equivalent disciplines that focuses on extensive use of data for analysis
• A minimum 5 years of experience participating in business intelligence and analytics projects as an individual contributor required
• A minimum 5 years of experience in data visualization tools (Tableau / PowerBI / Qlikview) is required
• A minimum 5 years of experience in SQL programming and standard MS Office applications is required
• Ability to analyze, identify, visualize and describe key trends within large datasets
• Hands-on experience with large volumes of data using SQL, Spark, Hadoop, or other big data ecosystems is preferred
• Practical knowledge in statistical and machine learning techniques including GLM, Regression, Random Forest, Boosting, Trees, Text Mining, Network analysis, etc. required.
• Practical knowledge in open source libraries such as scikit-learn, numpy, TensorFlow etc. is required.
• Good at requirements gathering, multitasking and work prioritization and being able to deliver work timely under pressure
• Understanding of banking, insurance, internal audit and financial services is preferred
• Curiosity & a real passion for understanding “why?”
• Creativity to see possibilities within the data & translate into compelling stories, decision and actions for non-technical business users
• Strong communication skills and ability to influence the business to take action using data