Audience Analytics Specialists

SPH MEDIA LIMITED; Singapore; On-site; SGD 90,000 - 140,000; Full time

Job summary

SPH Media Limited seeks data-driven Audience Analytics Specialists from Analyst to Senior Manager level to uncover insights about readers, subscribers and communities. You will transform raw data into strategic narratives guiding product, marketing and content decisions.

Responsibilities span data analytics, audience research, media measurement, and management reporting. Collaboration with editorial and business teams is essential to inform targeting and prioritisation, with a focus on

Qualifications

• 5+ years of hands-on experience in consumer research and analytics, business intelligence or marketing analytics.
• Proficiency in data visualization to build dashboards for stakeholders.
• Solid statistics foundation including cohort/funnel analysis, segmentation and hypothesis testing.
• Knowledge of marketing science methods such as MMM, attribution, incrementality testing and causal inference.
• Excellent storytelling and ability to translate analysis for non-technical stakeholders.
• Knowledge of Python or R for statistical analysis is a plus.

Responsibilities

• Collect, clean and analyse audience data from apps, websites, social media, paid advertising platforms and CRM systems.
• Ensure data accuracy, consistency and integrity across multiple data sources and platforms.
• Build and maintain user segments and personas based on consumption behaviours, demographics, engagement and LTV using advanced analytical models.
• Design and run qualitative and quantitative research (surveys, interviews, focus groups) to complement behavioural data with attitudinal insights.
• Uncover the why behind audience behaviours to add context to quantitative trends; synthesize findings into clear narratives.
• Design measurement frameworks such as incrementality testing and marketing mix modelling to isolate true causal impact.
• Build multi-touch attribution models that hold up across privacy-constrained environments.
• Apply causal inference methods to validate the real impact of media investments and experimental changes.
• Establish measurement standards, experiment governance and best practices across the organisation.
• Design and maintain dashboards and recurring reports to track audience growth, engagement, retention and churn.
• Automate recurring reporting workflows to improve accessibility for stakeholders across the organisation.

Skills

Data storytelling

Stakeholder communication

Cross-functional collaboration

Analytical thinking

Statistical thinking

Tools

Python

R

Data visualization tools

Job description

About the Role (Overall purpose of the job)

We're looking for data-driven Audience Analytics Specialists at all levels, from Analyst to Senior Manager, with a strong foundation in marketing science and measurement science, to uncover deep insights about our users, subscribers and communities. You'll turn raw, fragmented data into clear strategic narratives that shape product, marketing and content decisions - helping the business understand not just what audiences are doing, but why, and what to do next.

Roles & Responsibilities

Data Analytics

• Collect, clean and analyse audience data from apps, websites, social media, paid advertising platforms and CRM systems.
• Ensure data accuracy, consistency and integrity across multiple data sources and platforms.
• Build and maintain user segments and personas based on consumption behaviours, demographics, engagement and LTV using advanced analytical models.

Audience Research

• Design and run qualitative and quantitative research (surveys, interviews, focus groups, concept testing) to complement behavioural data with attitudinal and motivational insights.
• Uncover the "why" behind audience behaviours to add context to quantitative trends
• Synthesise research findings into clear narratives that combine "what" audiences do with "why" they do it.

Media Measurement

• Design measurement frameworks, such as incrementality testing and marketing mix modelling, to isolate true causal impact from correlation.
• Build multi-touch attribution models that hold up across privacy-constrained environments
• Apply causal inference methods to validate the real impact of media investments and experimental design changes
• Establish measurement standards, experiment governance and statistical best practices across the organisation.

Management Reporting

• Design and maintain intuitive dashboards and recurring reports to track audience growth, engagement, retention and churn.
• Automate recurring reporting workflows to reduce manual effort and improve data accessibility for stakeholders across the organisation.

Cross-Functional Collaboration

• Partner closely with editorial and business teams to inform audience targeting, messaging strategy, personalisation and roadmap prioritisation.
• Serve as a trusted advisor on measurement methodology helping stakeholders interpret results with appropriate statistical confidence
• Present insights and recommendations to both technical and non-technical stakeholders, including senior leadership.

Who we are looking for (Job Profile)

Work Qualifications

• At least 5 years of hands-on experience in consumer research and analytics, business intelligence or marketing analytics.

Required Experience

• Hands-on experience with media research, including audience measurement studies, ad effectiveness/brand lift studies, media mix and channel performance analysis, and syndicated research tools.
• Proficiency in using data visualisation tools to build clear, interactive, and stakeholder-ready dashboards and reports that communicate insights effectively.
• Solid statistics foundation, including cohort/funnel analysis, segmentation and hypothesis testing.
• Knowledge of marketing science methods, such as media mix modelling, attribution, incrementality testing and causal inference, to accurately measure media and marketing impact.
• Excellent storytelling skills; able to translate complex analysis into clear narratives for non-technical stakeholders.
• Knowledge of Python or R for statistical analysis, automation or predictive/causal modeling is a plus.