Responsibilities
- Collect, clean, and prepare large datasets from multiple sources such as sensors, databases, operational systems, and external data platforms.
- Develop and maintain data workflows or pipelines to ensure data is reliable, accessible, and ready for analysis.
- Apply statistical analysis, machine learning, and data mining techniques to identify trends, patterns, and operational insights.
- Build predictive models for forecasting, classification, regression, and optimisation use cases within utility or infrastructure operations.
- Work with time-series data, deep learning models, and image-based analytics where required to support advanced analytical projects.
- Create dashboards, reports, and visualisations to present findings clearly to internal stakeholders and external users.
- Monitor model performance and improve analytical solutions to enhance accuracy, reliability, and business impact.
- Support research and innovation initiatives by exploring new data science methods, technologies, and applications for operational efficiency and sustainability.
Requirements:
- Degree in Data Science, Mathematics, Statistics, Artificial Intelligence, Computer Science, or a related quantitative discipline.
- At least 1 year of hands-on experience in data science, machine learning, or real-time analytical projects.
- Proficient in Python, R, or SQL, with exposure to data analysis and visualisation libraries such as pandas, scikit-learn, matplotlib, or similar tools.
- Strong analytical thinking, problem-solving ability, and communication skills, with the ability to work with cross-functional teams and translate data into useful insights.
Please submit your updated resume in Word format by using the Apply Now Button.
We regret that only shortlisted candidates will be notified.
Email resume to [email protected]
People Profilers Pte Ltd, 20Cecil Street, #08-09, PLUS Building, Singapore 049705.
Tel: 6950 9724
http://www.peopleprofilers.com
EA License Number: 02C4944
Registration Number: R1872398
PostingPersonnel: Ng Jwee Ken
Ref: JOB-00717