Manager, Data and AI, Consumer Credit Oversight Board Task Force (CCOBTF)

Full Description

Role Purpose

Lead the development and execution of enterprise-wide data and AI strategy, governance, and operations, ensuring alignment with organisational objectives, while fostering a data-driven culture and building scalable AI capabilities across the organisation.

Principal Accountabilities

• Formulate and execute data strategy by developing enterprise-wide data strategy aligned with CCOB’sobjectives to ensure architecture scalability for the organisation’s future AI and analytics needs.

• Design future-ready data architecture and build scalable data warehouse integrating structured/unstructured data to ensure alignment with long-term business and AI requirements.

• Establish data governance framework through defining, advising and enforcing policies for data quality, security and compliance.

• Enable advanced analytics and AI by deploying predictive models and machine learning algorithms while maintaining analytics pipelines for real-time insights and support informed decision-making.

• Ensure strong data integrity and risk management by continuously monitoring data sources for accuracy and implementing proactive measures to prevent breaches and data loss.

• Strengthen data governance and security through maintaining operational data management, enforce data protection standards and apply pre-emptive risk management practices.

• Deliver actionable insights by providing intuitive dashboards and visual analytics, and translate these insights into clear, strategic recommendations for leadership.

• Foster a data-driven culture by promoting data literacy and responsible AI practices, to embed data-centric decision-making across the organisation.

• Lead team and develop high-performance teams through fostering collaboration and synergy across functions to achieve shared goals.

• Drive AI adoption and scalability by building organisational capabilities in AI.

Qualification and Experience

Academic Qualifications:

• Bachelor's in quantitative science discipline (e.g. Computer Science, Statistics, Applied Mathematics).

• Certifications in Data Engineering, AI/ML frameworks (TensorFlow, PyTorch), Cloud-based AI, are preferred.

Experience:

• Minimum of 8 years of experience in technology, data science or analytics, with proven expertise in managing data as well as some experience in AI initiatives

• Possess technical expertise and hands-on experience with Google Cloud Platform (GCP) technology stacks that includes BigQuery, Cloud Storage, Pub/Sub, Dataflow, Vertex AI, and Looker.

• Demonstrate strong knowledge of data architecture, data modelling, data analysis and visualisations techniques.

• Familiarity with AI and machine learning fundamentals as well as data governance and compliance frameworks.

• Demonstrates strategic thinking, business and digital acumen, adaptability and advanced problem-solving skills to lead data and AI initiatives.

• Technical Skills: ETL/ELT pipelines, SQL/NoSQL, Apache Spark, Kafka, predictive modelling and GCP technology services

ONLY SHORTLISTED CANDIDATES WILL BE NOTIFIED.