COMPANY DESCRIPTION
Singapore Management University is a place where high-level professionalism blends together with a healthy informality. The 'family-like' atmosphere among the SMU community fosters a culture where employees work, plan, organise and play together - building a strong collegiality and morale within the university.
Our commitment to attract and retain talent is ongoing. We offer attractive benefits and welfare, competitive compensation packages, and generous professional development opportunities - all to meet the work-life needs of our staff. No wonder, then, that SMU continues to be given numerous awards and recognition for its human resource excellence.
RESPONSIBILITIES
- Data Management and Analytics:
- Collect, clean and transform data from multiple internal and external sources, including APIs, space and booking management systems and smart meters.
- Build interactive and user-friendly dashboards, reports and data models to support business decision-making.
- Gather business requirements from different functional teams and translate them into suitable data requirements.
- Ensure data quality, consistency and governance across the organization.
- Conduct thorough data analysis to identify trends, patterns, and performance metrics that influence business decisions.
- Generate actionable insights through advanced analytics performed on diverse data gathered from large longitudinal cohorts, continuous sensors, and combined datasets.
- Develop compelling data-driven narratives for impactful storytelling to both internal and external stakeholders.
- Maintain library of OCIS data, reviewing sources of data, and recommend improvements to data sources and collection.
- Ensure data integrity and establish standardized reporting processes.
- Integrate OCIS data with broader university analytics to inform decision-making.
- Conduct usability audit on existing dashboards.
- Develop and optimize data models within the dashboarding tool for reporting and analytics.
- Optimize layout for clarity and user experience.
- Develop predictive models to forecast resource needs eg based on faculty expansion, student enrolment, and operational changes.
- Champion Experimentation:
- Design, implement, and analyse A/B tests and multivariate experiments to drive continuous improvement.
- Stay updated with the latest management technologies and automation tools.
- Propose, implement, and optimize technological solutions to enhance data analysis, reporting capabilities, and overall transportation efficiency.
- Stakeholder Engagement & Collaboration:
- Develop clear documentation of metric definitions and logic to ensure alignment across teams. Eg user Manuals and guidelines for stakeholders.
- Engage regularly with cross-functional stakeholders to understand their workflows, pain points, and evolving data needs.
- Translate business questions into actionable metrics and analytical solutions to support procurement and FMS operations.
- Collaborate with cross-functional teams to gather requirements, define data-related technical issues, and provide solutions.
- Provide user training and develop user guide and documentation.
- Automate manual processes and create efficient digital workflows.
- Support Environmental Sustainability in the Workplace:
- Collaborate with other teams on Sustainability related data and functions.
- Ensure alignment and accuracy of OCIS-provided data for organization-wide Sustainability reports.
- Participate in relevant meetings to understand stakeholder needs.
- Develop visuals that support communication and decision-making during Sustainability related meetings and reviews.
- Other duties as assigned.
QUALIFICATIONS
- Bachelor's degree or higher in Computer Science, Information Systems, Engineering, Business Analytics, Statistics or any related quantitative discipline/field.
- Other disciplines can be supplemented with additional qualifications and prior experience in Data Science / Data Analytics.
- 3 to 5 years of experience in Data Analytics, Business Intelligence, Data Engineering or relevant quantitative experience in the Real Estate / Facilities industry.
- Proficiency in data cleaning, analytics & visualisation tools (Power BI, Tableau, SQL).
- Good understanding of AI-driven scheduling and IoT-based tracking for real-time space monitoring.
- Strong proficiency in Excel and hands-on experience with querying and manipulating large, complex datasets with tools e.g. SQL, Python.
- Strong proficiency in statistical analysis and data mining techniques.
- Strong proficiency in Python (or R) for advanced statistical analysis, data modelling, and automation (e.g., pandas, numpy, scikit-learn).
- Proficiency with data visualization tools (e.g., Tableau, Looker, Power BI) to build effective and clear dashboards.
- Experience using dataflowgen 2/ Microsoft fabric.
- Experience writing PowerBI DAX function.