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Senior Manager, Digital Transformation

2 weeks ago

Bangsar South Kuala Lumpur, Malaysia AEON Credit Service (M) Bhd Full time 150,000 - 250,000 per year

Main Purpose of Job

The Head of Digital Transformation & Business Intelligence leads the enterprise-wide digital agenda and data-driven decision-making. This role designs and executes the strategy to build the foundation (governance, visualization standards, workforce upskilling), enable and scale BI and automation, integrate AI-driven insights and predictive analytics, optimize digital experiences with GenAI-powered BI assistants, and institutionalize digital intelligence including monetizing analytics services and embedding ESG-aligned practices across operations.

A. Corporate Digital Transformation

  • Lead and execute digital transformation strategies in alignment with corporate objectives and value drivers.

  • Digitize and automate end-to-end business workflows using process mining, RPA/low-code platforms, and integration services.

  • Embed change management, agile delivery, design thinking, and experimentation to build a digital-first culture.

  • Establish governance for digital initiatives with clear success metrics (OKRs/KPIs), benefits realization, and portfolio prioritization.

  • Track and report on transformation KPIs and business impacts to senior leadership.

B. Business Intelligence Strategy & Delivery

  • Develop and implement a comprehensive BI strategy aligned with the enterprise data strategy.

  • Define and maintain data visualization and dashboard standards; build a cross-domain enterprise BI dashboard library.

  • Deliver self-service analytics capabilities, semantic models, and governed datasets for business stakeholders.

  • Enable data literacy through training, communities of practice, and usage/adoption programs.

  • Manage BI platform architecture, release lifecycle, and service management (SLAs, support, continuous improvement).

C. Advanced Analytics & AI

  • Define and execute the AI & advanced analytics roadmap (predictive, prescriptive, forecasting, optimization).

  • Establish MLOps practices for model lifecycle: data preparation, feature engineering, training, deployment, monitoring, and governance.

  • Integrate AI-driven insights into BI products; deploy GenAI-powered BI assistants and natural-language analytics.

  • Champion responsible AI principles (fairness, transparency, privacy, security) and model risk management.

D. Data Governance, Architecture & Platforms

  • Support data governance framework including ownership, quality standards, cataloging, lineage, and access controls.

  • Partner with Data Architecture to deliver an enterprise data portal for governed self-service access (APIs, data marketplace).

  • Maintain a unified semantic layer and metadata standards to ensure consistency across domains.

  • Ensure compliance with data privacy, security, and regulatory requirements across jurisdictions.

E. Digital & BI Center of Excellence (CoE) & Change Management

  • Launch and lead the Digital & BI CoE, defining operating model, roles, processes, and funding.

  • Provide coaching and enablement to business units; establish guilds/chapters for analytics and automation.

  • Embed adoption within business processes through champions, governance forums, and incentives.

F. ESG & Sustainability

  • Integrate ESG data and metrics into BI and reporting; support frameworks (e.g., GRI, SASB) and assurance needs.

  • Embed sustainable, responsible digital practices across operations (energy efficiency, ethical AI, inclusive design).

G. Commercialization & Monetization of Analytics

  • Develop and manage internal/external analytics products and services; define value propositions and pricing.

  • Establish commercialization KPIs (usage, revenue, margin) and manage SLAs with business stakeholders and partners.

H. Digital Experience & Adoption

  • Enhance customer and employee digital experiences via journey mapping, personalization, and AI-enabled assistance.

  • Measure and improve satisfaction (CSAT/NPS), task completion, and time-to-decision through digital channels.

I. Risk, Compliance & Ethics

  • Ensure compliance with relevant regulations and internal policies for data, AI, and digital platforms.

  • Lead risk assessments for digital solutions; implement controls for model, data, and operational risks.

J. Performance & Reporting

  • Define measurement framework and dashboards to track digital transformation, BI adoption, automation gains, and business impact.

  • Report progress to senior leadership and continuously refine the roadmap based on outcomes.

Requirements:

  • Bachelor's or Master's degree in Business, Information Systems, Computer Science, Data Science, or related field.

  • Minimum 10 years of experience leading digital transformation and BI programs; experience in regulated industries is an advantage.

  • Deep knowledge of digital technologies, cloud computing, agile delivery, process automation (RPA/low-code), and customer-centric design.

  • Hands-on experience with enterprise BI platforms (e.g., Microsoft Power BI or equivalent) and data visualization best practices.

  • Proven track record delivering AI/ML and predictive analytics solutions; familiarity with MLOps and GenAI applications.

  • Experience establishing data governance frameworks, semantic models, and enterprise data portals/self-service architectures.

  • Demonstrated ability to commercialize analytics services/products; financial acumen (business cases, pricing, ROI).

  • Strong stakeholder engagement, communication, and change leadership skills; ability to balance strategic vision with hands-on execution.

  • Commitment to responsible AI, data ethics, sustainability, and ESG reporting practices.