Text Analytics and Processing

1. Supports the production of scalable and optimised artificial intelligence (AI)/machine learning (ML) models. 2. Focuses on building algorithms for the extraction, transformation, and loading of large volumes of real-time, unstructured data to deploy AI/ML solutions from theoretical data science models. 3. Runs experiments to test the performance of deployed models and identifies and resolves bugs that arise in the process. 4. Works in a team setting and is proficient in statistics, scripting, and programming languages required by the organisation. 5. Familiar with the relevant software platforms in which the models are deployed. 6. Knowledgeable of the requirements under the Model AI Governance Framework and the Personal Data Protection Act (PDPA) in his work on AI/ML models. 7.Determined individual comfortable working with large data sets, keen interest in problem solving and experimentation.

1. Analyze customer data specific to the telecommunications industry, including usage patterns, service preferences, and satisfaction levels. 2. Utilize advanced analytics and statistical methods to segment customers and predict behaviors such as churn, upsell opportunities, and service adoption. 3. Collaborate with cross-functional teams, including marketing, sales, and product development, to leverage customer insights for targeted campaigns and product enhancements. 4. Monitor and assess the impact of telecommunications market trends on customer behavior and expectations. 5. Develop and maintain dynamic reports and dashboards that provide actionable insights into customer demographics, behaviors, and lifecycle stages. 6. Conduct customer journey mapping to identify key touchpoints and opportunities for improving the customer experience. 7. Design and implement customer surveys, focus groups, and other research initiatives to gather qualitative insights. 8. Provide data-driven recommendations to inform customer retention strategies and loyalty programs. 9. Communicate complex analytical findings to non-technical stakeholders in a clear and compelling manner. 10. Support the creation of personalized customer communications and offers based on data-driven segmentation and profiling.

1. Plans and leads the development of new and advanced data analytic techniques, methodologies and analytical solutions from design, prototyping, and testing. 2. Identifies and develops core data and artificial intelligence (AI) science components for the delivery of projects, architects specialised database and computing environments, explores and visualises complex data set to provide incremental business value. 3. Extracts and integrates data from various sources, and creates advanced models and algorithms suitable for the business use case. 4. Conducts testing on data and AI models, interprets findings from testing, and evaluates model performance for scaling and deployment. 5. Develops compelling and logically structured communication materials to facilitate stakeholder buy-in. 6. Works in a team setting and is proficient in statistics, scripting and programming languages required by the organisation. 7. Familiar with the relevant software platforms on which the solution is deployed. 8. Has strong analytical and critical thinking skills to identify and solve problems. 9. Passionate about analysing and resolving complex business problems, displays intellectual curiosity towards using data and AI to address business needs and challenges. 10. A data storyteller, able to influence key stakeholders and spearhead a data-driven approach to resolve business issues.

1. Formulates and implements data and artificial intelligence (AI) strategies to optimise business value derived from data assets. 2. Guides the AI research direction to create new algorithms and models, and reviews the feasibility of translating research and development outcomes into data and AI solutions. 3. Oversees the development of data and AI solutions for the business to inform strategy and planning, decision-making, and drive performance. 4. Identifies potential intellectual property commercialisation opportunities for AI solutions and/or models, and oversees the preparation and application for intellectual property rights. 5. Manages a team and is proficient in statistics, scripting, and programming languages required by the organisation. 6. Familiar with the relevant software platforms on which the solution is deployed. 7. Highly effective communicator, articulating the potential value and impact of data and AI solutions on the business and influencing key business stakeholders. 8. Proactive and innovative individual, possessing a strong drive to succeed amidst an evolving business environment. 9. Develops the data and AI team's technical and leadership capabilities and ensures compliance to the organisation's data privacy policies, ethics and governance framework, and intellectual property legislation.