This role will require him/her to support in the following tasks:
- Work closely as part of the agile product team to design, develop, test and deploy data analytics/scientist products (e.g. interactive dashboards, reports and machine learning models) under the guidance of the DSTA Product Manager.
- Conduct detailed requirements gathering and clarify requirements with the end users, when required, to formulate, translate and refine their business questions into technical and analytical requirements.
- Carry out data audits and technical feasibility assessments.
- Design and develop data analytics/scientist products with the necessary authorisation mechanisms and measures to meet business, user experience, performance and security requirements, using established processes and tools on the Authority’s Enterprise Data Analytics Platform.
- Work closely with relevant technical teams (e.g. Enterprise Data Analytics Platform team, Data Integration team, Database team etc.) during design, development, system integration, testing and deployment, implementing changes if required.
- Perform vulnerability assessments and code quality tests where applicable. Rectify any vulnerability or code quality issues surfaced.
- Conduct User Acceptance Tests based on acceptance criteria in Product Backlog, review feedbacks received and include them in the Product Backlog for prioritisation if applicable.
- Conduct end-user training, handover training and product demonstrations.
- Provide on-site support to troubleshoot any problems and address users’ queries relating to deployed data analytics/scientist products (interactive dashboards, reports and machine learning models).
- Develop and maintain documentations according to the Authority’s Quality Management System (QMS) guidelines (e.g. user guide, design specifications).
- Work with end-users to explore and analyse data for trends and insights relating to user business questions.
- Maintain existing dashboard for additional indicators/charts including raising Service Request (SR) for data extractions.
Qualifications:
Relevant educational credentials in a quantitative discipline (e.g. statistics, computer science, data science/analytics/engineer, or information systems)