SPH - Data Analyst, Behavourial Analytics (Consumer Division)

Location: Singapore
Business sector: Data Analytics
Job reference: 864676
Published: about 2 months ago
To support the fast-growing data analytics team within Consumer Division, we are looking for a competent Data Analyst to join the team in providing digital user behaviour insights on our websites and apps, to drive new subscriptions and increase monthly active users.
 
This Data Analyst will be deriving insights and developing dashboards with internal and external data, including but not limited to marketing and engagement campaigns, conversion levers and checkout flows. This role is expected to be highly independent, support insights projects through the entire analytics lifecycle, and be the glue between business and data.
 
This role will be expected to go beyond being an “analyst”. This involves understanding how different systems work, read through systems documentation on data endpoints, work with Tech to plan user behaviour tracking requirements, handle UAT to test those tracking plans, write automated ETL scripts, understand marketers’ user requirements and build/maintain the dashboards required. Recording of checks to ensure accuracy of data/insights before presentation to stakeholders will be a basic expectancy for this role.
 
This role will partake in new ideas and face unknowns that come with changing business demands and technical industry trends. The Analyst must be willing to explore & tackle said unknowns, and be involved in cross functional projects to ensure data related to CD data objectives are well-governed.
 
 
Roles & Responsibilities
 
Data acquisition
  • Support Division’s need for subscriptions and revenue related data dimensions and metrics.
  • Work closely with other stakeholders from SPHTech to source for new behavioural/ demographic data dimensions and metrics relevant for the Division’s growth.
  • Liaise with data engineers from SPHTech to ensure healthy ETL of the Division’s behavioural metrics.
Data documentation and accuracy
  • Maintain high quality and proper documentation of analytical work done.
  • Ensure your work, including analysis and insights are accurate and validated.
Data analysis, insights and forecast
  • Contribute to analytical insights of behavioural metrics, including but not limited to content consumption, paywalls and checkout flows.
  • Collaborate with the commercial analytics team to draw end-to-end insights of our readers and customers.
Dashboards
  • Develop and maintain dashboards that track the readers and customer’s behavioural journey to inform marketing campaigns.
  • Collate and act on feedback from stakeholders to continuously ensure that the dashboard product serves the Division’s needs.
 
 
Requirements
 
  • Proficient with at least one dashboard / business intelligence tool (e.g. Google Lookerstudio or Tableau). AWS Quicksight is preferred.
  • Work experience in data extraction and EDA using SQL and Python (with Jupyter Notebooks or Visual Studio Code).
  • Work experience with AWS Glue, Pyspark for scheduled ETL processes will be a bonus.
  • Experience with machine learning/modelling is a bonus.
  • Work experience with Google Analytics 360, Google Analytics 4, Google Tag Manager will be a bonus.
  • Work experience in creating compelling data reports, drawing actionable insights & visualisations.
  • Strong data storytelling and presentation skills, with the ability to communicate findings in a clear and actionable manner.
  • Proficient with spreadsheets.
  • Familiarity with marketing performance tracking and A/B testing concepts.
  • Domain knowledge on subscription business models is a bonus.
  • Exposure and understanding of digital media industry metrics is a bonus.
  • Track-record of independent learning and problem-solving.
  • Keen interest in stakeholder management from various backgrounds, including data engineers and product/ platform owners.
  • Good time and project management skills, able to multitask, and most importantly willingness to learn.
  • At least 1 year of experience in data analytics.
  • A good university degree in Statistics, Engineering, Economics, Mathematics, Physics, Computer Science, Business Administration or related fields.