Our client is a global leader in the water and waste sectors and we are seeking a Data Scientist to join their growing digital solutions team.
In this role, you will leverage advanced analytics, machine learning, and artificial intelligence to develop innovative solutions that improve water utility operations, environmental sustainability, and infrastructure performance. You will work with large and diverse datasets to uncover actionable insights, build predictive models, and develop data-driven solutions that address complex operational challenges.
The ideal candidate has a strong foundation in data science and machine learning, enjoys solving real-world problems, and thrives in a collaborative, multidisciplinary environment. You should be comfortable working with large datasets, developing analytical models, and communicating technical findings to both technical and business stakeholders.
Key Responsibilities
Data Collection and Processing
- Collect, clean, and pre process large volumes of data from various sources, including sensor networks, databases, and external datasets related to water usage, quality, and infrastructure.
- Develop and maintain data pipelines to ensure the availability and integrity of data for analysis and modeling purposes.
Data Analysis and Modeling
- Use standard and advanced data scientist approaches: time series modelling, machine learning technics for regression and classification, deep learning models for forecasting, computer vision models for images analysis.
- Apply statistical analysis, machine learning, and data mining techniques to extract meaningful patterns, trends, and correlations from water utilities operation data.
- Build predictive models to forecast water demand, develop and deliver solutions proposed by SUEZ related to environmental protection (resource optimisation, flood prevention, etc.)
Visualization and Reporting
- Create visualizations, dashboards, and reports to communicate insights and findings to stakeholders, including government officials and water utility operation managers.
- Collaborate with stakeholders to understand their requirements and tailor analytical outputs to meet their needs.
Performance Monitoring and Optimization
- Monitor the performance of data models and analytical solutions, conduct ongoing evaluation, and implement improvements to enhance accuracy and reliability.
- Work on optimisation projects aimed at improving the efficiency and sustainability of water management practices, such as reducing water loss and energy consumption. General
Research and Innovation
- Stay abreast of the latest developments in data science, water management technologies, and regulatory frameworks.
- Conduct research and experimentation to explore innovative approaches and emerging technologies applicable to water utilities.
Required Skills & Qualifications
- Bachelor's degree in Data Science, Mathematics, Statistic, Artificial Intelligence or related quantitative field
- At least 1 year of experience developing real-time projects in Machine Learning and Data Science.
- Solid understanding of data analysis, statistical modeling, and machine learning techniques.
- Proficiency in programming languages such as Python, R, SQL, and familiarity with data manipulation and visualization libraries (e.g., pandas, scikit-learn, matplotlib, seaborn).
- Engineer skills are not needed, but the candidate is expected to be able to write simple code to prototype and test analytical ideas
- Strong problem-solving skills, critical thinking, and attention to detail.
- Excellent communication skills and ability to collaborate effectively with interdisciplinary teams and stakeholders.
- Adaptability and willingness to learn new concepts and techniques in a dynamic work environment.
Timeo-Performance Pte Ltd
9 Raffles Place, Republic Plaza #06-00 Singapore 048916
EA Licence: 21C0685âEA Personnel Number: R1103259
IMD International Search Group â Asia Partner
Timeo-Performance is committed to fair and merit-based recruitment. We consider all qualified applicants regardless of age, gender, marital status, family responsibilities, race, religion, nationality, or disability, in line with the Tripartite Guidelines on Fair Employment Practices and the Workplace Fairness Act.
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