Manager to Senior Manager, Analytics & Insights

STB - TOURISM COURT BUILDING

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[What the role is]

The Manager at Analytics & Insights team will play a pivotal role in using data to guide planning and/or strategies of stakeholders in addressing business problems and determining opportunities of growth for Singapore’s tourism industry. This role will be responsible for all aspects of the data lifecycle, including as a data custodian, leveraging data analytics to distill findings to answer key business questions and uncover new opportunities for the business. With a strong knowledge of quantitative market research methodologies, the individual will have the opportunity to collaborate with business users to assess the impact of tourism products and experiences.

[What you will be working on]

1. Data Analytics

a) Apply data mining & statistical techniques to process and analyse datasets. This may require working with large, complex datasets, integrating multiple data sources and/or collaborate with our Data Engineers to enhance our data pipelines.

b) To share insights that addresses business questions through visualisations.

2. Project Management

a) Be a data custodian of key datasets managed by the team. You will act as the in-house subject matter expert and is required to work closely with both external and internal stakeholders to manage the data.

b) Collaborate with internal and external stakeholders, such as WOG personnel, industry stakeholders and vendors as relevant to ensure smooth project implementation.

 

3. Data Support & Advisory

a) Understand key business and research outcomes of stakeholders and provide timely advice and support to stakeholders.

b) Provide sound quantitative research advisory, including but not limited to research methodology, questionnaire design, data collection approach, data quality, data pre-processing, data management and analysis.

c) Drive economic impact assessment and cost benefit analysis of projects within STB, working closely with stakeholders within STB & WOG.

 

4. Data Capability

a) Lead, manage and drive greater use of data among business users to answer business questions.

b) To share best practices with the aim of uplifting data capability.

[What we are looking for]

  • Degree from a recognised university in a quantitative discipline: Data Analytics, Data Science, Applied Mathematics or Statistics, or a related discipline
  • At least 5 years of relevant experience in data collection, data pre-processing, data wrangling, and data visualisation
  • Experience in modelling, creating, editing and publishing dashboards using visualisation tools such as Qlik Sense is advantageous
  • Strong analytical skills with a good eye for detail and possess an aptitude/experience in solving analytical problems using quantitative approaches
  • Ability to communicate clearly complex data/concepts and outcomes of analysis so that learnings can be translated into strategies
  • Ability to integrate and synthesise research and data across multiple sources to derive meaningful conclusions
  • Strong organisation, project and time management skills
  • Working experience in managing projects with external stakeholders and vendors
  • Experience working with cross-functional teams in a dynamic, fast-paced environment
  • Good mastery of both quantitative and qualitative research methodologies
  • Strong presentation and communication skills with ability to express complex ideas in an easy-to-understand manner
  • Mature and comfortable presenting to and interacting with people from senior management levels
  • Strong command of written and spoken English
  • Possess statistical knowledge and comfortable working with numbers
  • Proficient in data manipulation using R, Python and SQL
  • Proficient in Advanced Excel, PivotTable and Power Pivot 
  • Working experience in QlikSense and AWS services will be advantageous.
  • Proven track record in engaging relevant stakeholders (within and outside of the organisation)
  • Experience in managing project teams

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Tags: AWS Data Analytics Data management Data Mining Data pipelines Data quality Excel Market research Mathematics Pipelines Python Qlik R Research SQL Statistics

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