Senior Data Intelligence Analyst

Publicis Groupe ANZ; Singapore; On-site; SGD 90,000 - 150,000; Full time

Job summary

Publicis Groupe ANZ is seeking a Senior Data Intelligence Analyst to join our regional Data Intelligence team. You will interrogate and transform data using SQL, create dashboards in Power BI or Looker, and apply AI-enabled analysis to deliver actionable business insights across markets.

You will test data reliability, identify anomalies, and benchmark data to translate complex findings into business recommendations.

Qualifications

• 3-5 years of relevant experience in data analytics or related fields.
• Strong SQL skills with experience handling large datasets.
• Experience with Power BI or Looker/Looker Studio.
• Proven experience using AI tools for analytics and workflow improvements.
• Ongoing development in AI and data analytics through courses or projects.

Responsibilities

• Query, clean and transform large datasets across multiple markets and sources.
• Develop dashboards and visualisations using Power BI or Looker Studio.
• Analyse digital media, competitive intelligence and market data for trends and insights.
• Evaluate data quality and reliability using validation, benchmarking and stats.
• Develop data normalisation, estimation and benchmarking methods across sources.
• Apply AI-enabled analytical tools to accelerate analysis and QA.
• Use AI-assisted coding and automation to reduce repetitive work and improve consistency.
• Maintain rigorous QA standards and document methodologies.

Skills

SQL

Power BI

Looker Studio

AI tools for analytics

Data visualization

Excel

Data analytics

BigQuery

Stakeholder communication

Tools

BigQuery

Job description

Company description

We are seeking a Senior Data Intelligence Analyst to join our regional Data Intelligence team. The role combines data analytics, competitive intelligence, AI-enabled analysis and project delivery, working with large and often complex datasets across multiple markets and sources.

The successful candidate will be comfortable interrogating and transforming data using SQL, developing analysis and visualisation through Power BI or Looker/Looker Studio, and using modern AI tools to improve the speed, quality and sophistication of analytical work.

A key part of the role is not simply reporting data, but testing its reliability, identifying anomalies and inconsistencies, comparing multiple sources, developing appropriate benchmarks and normalisation approaches, and translating complex findings into clear business recommendations.

We are particularly interested in candidates who actively use AI and automation to solve analytical problems and who can demonstrate continued learning through practical experience, courses, certifications or personal/professional projects.

Responsibilities

Data Intelligence & Analytics

• Query, combine, clean and transform large and complex datasets using SQL, including data from multiple platforms, markets and third-party sources.
• Develop dashboards, analytical outputs and data visualisations using Power BI or Looker/Looker Studio.
• Analyse digital media, competitive intelligence and market data to identify trends, anomalies, relationships and actionable insights.
• Evaluate the quality, accuracy and reliability of different data sources using appropriate validation, correlation, benchmarking and statistical techniques.
• Develop and improve data normalisation, estimation and benchmarking methodologies across markets and data sources.
• Apply AI-enabled analytical tools and techniques to accelerate analysis, improve QA, investigate data issues and generate deeper insights.
• Use AI-assisted coding and automation where appropriate to reduce repetitive manual work and improve analytical consistency.
• Maintain rigorous QA standards and clearly document methodologies, assumptions and limitations.

AI, Automation & Innovation

• Demonstrate practical experience using generative AI and AI-assisted analytical tools in a professional, academic or project environment.
• Identify opportunities to automate repetitive data preparation, QA, analysis and reporting processes.
• Keep abreast of emerging AI and analytics capabilities and assess how they can practically improve products and workflows.
• Contribute to the development of scalable analytical methods, tools and processes across the regional team.

Project Management & Collaboration

• Lead and support the end-to-end delivery of analytics and reporting projects across local and regional teams.
• Manage timelines, documentation, QA checks and cross-functional coordination to deliver high-quality outputs.
• Partner with internal teams, clients and external data vendors to gather requirements, present insights and resolve analytical issues.
• Balance strategic priorities with ad-hoc analytical requests and comfortably manage multiple projects simultaneously.
• Identify and implement process improvements that strengthen the quality, efficiency and scalability of analytics delivery.

Qualifications

• 3-5 years of relevant experience in data analytics, data intelligence, business intelligence, digital media analytics or quantitative research.
• Strong practical SQL skills and experience working with large datasets. Experience with BigQuery or a similar cloud data environment is desirable.
• Strong experience with at least one of Power BI or Looker/Looker Studio.
• Demonstrable practical experience using AI tools for analytics, research, problem-solving or workflow improvement.
• Evidence of ongoing development in AI and data analytics through recognised courses, certifications, professional training or substantial hands-on projects.
• Strong analytical reasoning, including the ability to validate data, investigate discrepancies, compare sources and assess whether analytical outputs make sense.
• Good understanding of digital marketing metrics, competitive intelligence and/or quantitative market research.
• Advanced Excel skills and the ability to communicate complex analysis clearly through PowerPoint.
• Proven ability to manage multiple analytical projects and communicate effectively with technical and non-technical stakeholders.
• Detail-oriented, proactive and solution-driven, with a strong commitment to data quality and accuracy.