Position Overview
The Chief Data Officer (CDO) will be responsible for the development and implementation of AEON Credit Service (M) Bhd's data strategy, ensuring the organization maximizes the value of its data assets while ensuring compliance, privacy, and security standards. This newly created position will focus on driving data innovation, governance, analytics, and business intelligence initiatives, with a strong emphasis on improving operational efficiency, customer insights, and decision-making across the organization.
Key Responsibilities:
Data Strategy Leadership:
- Develop and execute a comprehensive data strategy that aligns with AEON Credit Service's business goals, vision, and objectives.
- Lead the creation and management of data-driven initiatives to enhance customer experience, financial products, and services.
- Establish the vision for data as a strategic asset and promote a data-driven culture across the organization.
Data Governance and Compliance:
- Define and enforce data governance frameworks, policies, and best practices to ensure data quality, privacy, and security, in line with relevant industry standards (e.g., PDPA, GDPR).
- Ensure the company adheres to all regulatory and compliance requirements related to data management, with particular focus on the financial services industry.
- Develop protocols for data access, retention, and disposal to manage risk and safeguard sensitive financial data.
Data Analytics & Business Intelligence:
- Drive the use of data analytics to unlock business insights, identify trends, and recommend actionable strategies for business growth and efficiency.
- Oversee the development and maintenance of advanced analytics models and business intelligence tools for decision-makers.
- Guide the integration of data-driven insights into core business processes, especially in areas like credit risk management, fraud detection, customer segmentation, and marketing.
Data Infrastructure & Technology:
- Lead the development of scalable data infrastructure and architecture to support enterprise-level analytics, machine learning, and big data initiatives.
- Collaborate with IT and technology teams to evaluate and implement modern data management tools, platforms, and technologies.
- Ensure the optimization and automation of data pipelines for efficient data flow and processing.
Team Leadership and Development:
- Build, lead, and mentor a high-performing data team, including data engineers, data scientists, and analysts.
- Foster a collaborative, innovative environment that encourages continuous learning and development of data talent.
- Define key performance indicators (KPIs) for data teams and ensure the alignment of resources with business priorities.
Cross-functional Collaboration:
- Work closely with key business units such as marketing, risk management, finance, and operations to identify data-driven opportunities for improvement.
- Provide data expertise and guidance to senior leadership, ensuring data-centric decisions are made at the executive level.
Qualifications:
- Bachelor's or Master's degree in Computer Science, Data Science, Information Technology, Statistics, Business, or a related field.
- Additional certifications in data management, data science, or analytics are preferred.
- Minimum 10-15 years of experience in data management, with at least 5 years in a senior leadership role (e.g., Director, VP, or Head of Data Analytics, Data Science, or Business Intelligence).
- Strong background in the financial services or credit industry is a significant advantage.
- Demonstrated experience in building and scaling data teams, driving data governance, and managing complex data ecosystems.
- Expertise in data analytics, business intelligence tools, and technologies such as SQL, Python, Hadoop, Spark, AWS, etc.
- Experience in leading enterprise-wide data transformation initiatives.
Skills & Competencies:
- Strong knowledge of data privacy and security regulations, especially in financial services.
- Proven ability to translate business goals into actionable data strategies.
- Excellent communication skills, with the ability to present complex data concepts to non-technical stakeholders.
- Strategic thinking with a hands-on approach to problem-solving and decision-making.
- Strong project management and organizational skills, with the ability to prioritize and manage multiple projects simultaneously.
- Familiarity with advanced analytics techniques, machine learning, and AI applications in business contexts.
