JOB SUMMARY
Lead a variety of data analytics and AI initiatives, collaborating with stakeholders to identify business analytics requirements and deliver actionable insights that advance the agenda of data-driven decision-making. Uncover valuable information within large datasets to enable more informed decisions. Drive AI initiatives to promote and enhance the adoption of AI technologies across the company.
KEY DUTIES AND RESPONSIBILITIES
- Spearhead data analysis and a range of data analytics projects, including reporting, modeling, and business intelligence initiatives.
- Lead collaboration with stakeholders to identify business requirements and expected outcomes, with a focus on improving efficiency, productivity, and monetization through various data science methodologies.
- Predictive modelling efforts for planning capital work, distribution, production, Non-Revenue Water and other operational areas.
- Develop real-time event triggers and predictions using sensor analytics, image analytics, video analytics, network analytics, and related technologies.
- Apply data mining techniques, conduct statistical analyses, and build high-quality predictive systems integrated with our water solutions.
- Continually enhance the advanced analytics program by staying abreast of the latest developments in data science, advanced analytics, statistical programs, and big data methodologies.
- Work with and lead vendors and consultants on various analytics and AI projects, ensuring best practices are applied for internal usage.
- Collaborate with units within the Data Analytics Centre and other departments to support data collection, integration, and retention requirements.
- Lead, manage, guide, and coach team members to continuously develop and upscale analytics skill sets.
- Drive AI initiatives by identifying opportunities to implement artificial intelligence solutions across the organization, promoting the adoption and integration of AI technologies to advance data-driven decision-making.
- Champion the evaluation, selection, and deployment of AI tools and platforms that align with business objectives and enhance operational efficiency.
- Foster a culture of innovation by encouraging the exploration and application of emerging AI methodologies and technologies.
- Partner with cross-functional teams to develop and implement AI-powered solutions that deliver actionable insights and measurable business impact.
- Monitor and assess the effectiveness of AI initiatives, ensuring continuous improvement and alignment with organizational goals.
PERSON SPECIFICATION
Minimum Qualifications
- At least a bachelor degree in any of the following: Data Science, Computer Science, Mathematics, Statistics, Economics, Actuarial
- At least 8 years working experience of relevant quantitative research and analytics experience.
- Experience with SQL / Phyton / SAS / Tableau / R / SPSS or other Machine Learning programming languages.
- Proficient in Machine Learning, Artificial Intelligence including Gen AI and Agentic AI.
- Proficient in statistical analysis, quantitative analytics, forecasting/predictive analysis and operations research.
- Leadership or Management of team members in the past employment.
- Experience in cloud platforms, Azure, GCP, AWS, Alibaba Cloud etc.
Knowledge, Experience, Skills & Abilities
- Knowledge of data acquisition, statistics and other mathematical modeling methodologies.
- Knowledge of Machine Learning, Deep Learning, Generative AI and Agentic AI.
- Knowledge of statistical techniques and proficiency in the use of statistical package.
- Knowledge of business vs analytics - understanding data from various systems for deeper comprehension on data structure based on subjects.
- Preferably to have attended Big Data Analytics short-term courses or have obtained certification in Data Science.
- Proficient in statistical analysis, quantitative analytics, forecasting/predictive analysis and operations research.
- Developing stakeholder-ready deliverables and presenting them with confidence and influential.
- Skill of creating Machine Learning model, including data cleansing, data transforming, feature engineering, hyper-parameter turning, model evaluation and model deployment.
- Skill of implementing use cases using Machine Learning, Deep Learning, Statistical Model, Generative AI and other algorithms.
- Ability to lead, plan, and deliver strategic analytics initiatives across multiple business units.
- Able to complete multiple tasks within the deadline.
- Ability to work closely with stakeholders to understand business challenges and convert them into data-driven solutions.
