Senior Manager, Digital Transformation & Business Intelligence

AEON Credit Service (M) BerhadKuala Lumpur, Kuala Lumpur, Malaysia

17 days ago

Job description

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.

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.

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.

Seniority level

Mid-Senior level

Employment type

Full-time

Job function

Information Technology

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