Data Scientist
3 days ago
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)
Tell employers what skills you haveTensorFlow
Machine Learning
Analytical Chemistry
Dashboard
Data Analysis
Big Data
Quality Management
HPLC
Natural Language Processing
Hadoop
Artificial Intelligence
User Experience
Data Integration
Python
Statistics
Data Science
Visualization
System Integration Testing
Data Analytics
Data Visualization
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