Data Science & AI Director
Location: West
Working Hours: Monday - Thursday (8.30AM - 6.00PM), Friday (8.30AM - 5.30PM)
This incumbent is responsible to lead in the research & development, strategy, architecting, planning and delivery of data science capabilities (e.g. Artificial Intelligence Engineering, Data Engineering, Cognitive Computing and Decision Science), to transform and support the organisation’s overall sense making capabilities.
Responsibilities:
(1) Support the organisation’s transformation into a data-driven organisation by charting the strategic directions to design, develop and deliver Data and Analytics capabilities that includes:
- Transform the team to deliver next-generation data and analytics capabilities that support rapid on-boarding of data sources, high-scalable architecture that empower both employees and data scientist to self-serve to a suite of data products, ranging from data-self-serve to analytics-as-a-service.
- Develop organic Data Engineers for improved data management, to ingest data, design and architect data pipelines, data architectures for different data consumer groups.
- Develop organic Data team to exploit all data to harness new insights and support better sense making capabilities.
- Develop roadmaps to deliver cutting-edge sense making capabilities that harness all data types such as high velocity, structured, unstructured, images, videos, geo-location, signal, etc.
- Drive data analytics and AI/ML models for big data analytics, and advance dashboarding for data and insights visualisation, including GIS and LLM/GenAI technology.
- Guide new data-driven approaches for the purpose of generating operational insights that address operational challenges in a proactive manner.
- Collaborations with partners and stakeholders to research in advance AI/ML model to solve complex and/or wicked problem statements beyond Data Science, when no readily available solution can be found in the market.
- Proliferate and upskill Data Science competencies within organisation, including supporting relevant training to upskill data analysis/data science proficiency levels.
(2) Ensure timely delivery and implementation of the enterprise data and sense making projects that include data architectures (ingestion, storage, acquisition, validation), data exchanges, big data analytics platforms, user data and analytics systems.
(3) Lead strategic discussions with senior management and key stakeholders to ensure successful delivery of projects and capabilities.
(4) Act as the organisation’s Chief Data Officer and drive the following initiatives:
- Work with governance units to ensure data security governance complies with the prevailing policies and addresses all matters relating to data governance and solutions required to ensure secured, timely and efficient delivery of data to the respective stakeholders.
- Drive the management, use and sharing of data in a secure manner, and plug any gaps to comply with organisation guidelines.
- Define the organisation’s data strategy, goals, polices and management of organisation’s data assets, and coordinate returns for organisation’s indices.
- Raise the staff’s awareness on data policies, procedures and promote culture of data privacy and security.
- Drive data analytics adoption within the organisation and promote data-driven business decisions.
(5) Work with users to identify appropriate Data Science solutions to better users’ current outcomes, bring new or additional value to their operations, and/or create new/transformative capabilities for the users, such as:
- Lead users and diverse stakeholders to understand and identify users’ challenges and co-define problem statements where Data Science solutions can mitigate these challenges.
- Work with users and multi-disciplinary technical/specialist teams to scope and formulate problem statements and identify the appropriate Data Science solutions to achieve the best outcomes to these problems.
- Manage the proper resourcing of projects with the right people with the right competencies and expertise; influence and negotiate with stakeholders to secure the required resources.
- Degree in Engineering/Computer Science/Information Technology or relevant disciplines.
- Relevant working experience in IT environment including a minimum of 8 years in a leadership position managing data analytics and/or Data/AI product development team.
