The Role
Lead strategy and execution for data and AI to drive revenue, cost savings, and customer outcomes. Build governance (PDPA), oversee ML deployment and data platforms, manage budget and KPIs, foster innovation, mitigate AI risks, and develop a high-performing data team aligned with senior leadership.
Summary Generated by Built In
Are you ready to get ahead in your career?
- We want to empower you to turn your ambitions into achievements.
- We thrive in inclusiveness, diversity and embrace close collaborations for you to create impact for yourself and others.
- Together, we aim to bring the best of technology to help people, businesses and the nation to be ahead in a changing world.
- To realise our vision to become Malaysia’s leading converged solutions company, we are looking for a new talent to innovate and grow with us in a culture that values commitment, performance and possibilities.
Why does this job exist and why is it critical?
Principal Accountabilities:- Strategic Leadership & Value Generation: Formulate and execute a long-term strategic vision and roadmap for data and AI capabilities that directly contributes to revenue growth, cost efficiency, and customer satisfaction.
- Advocacy and Collaboration: Act as a key advocate for data-driven decision-making and sustainable value generation, liaising directly with senior leadership teams (SLTs) and the Maxis Management Team (MMT) to ensure data and AI initiatives are fully aligned with and support overall business objectives.
- Business Outcome Focus: Lead the development and deployment of data and AI initiatives that are directly tied to tangible business outcomes and key performance indicators.
- Innovation and Research: Promote a culture of innovation by investigating new AI technologies and methodologies to address complex business challenges and create sustainable value.
- Data Governance: Develop and implement robust data governance frameworks to ensure data quality, privacy, and regulatory compliance (including PDPA) across the organization.
- Talent Management: Guide and cultivate a high-performing team of data scientists, engineers, and analysts, ensuring continuous skill enhancement and career development.
- Performance Measurement: Establish, monitor, and report on key performance indicators (KPIs) to evaluate the direct impact of data and AI initiatives on business results and strategic goals.
- Risk Management: Identify and mitigate risks associated with data and AI applications to uphold ethical and legal standards, ensuring responsible AI practices.
- Budget Oversight: Develop and manage the budget for data and AI functions, ensuring optimal resource allocation to maximize return on investment.
- Financial Impact: Quantifiable increase in revenue or reduction in operational costs attributed to data and AI-driven initiatives.
- Strategic Growth: Successful launch and adoption of new data products or AI solutions that open up new market opportunities or enhance customer engagement.
- Data-Driven Insights: Increase in the number of actionable insights provided to business units and the rate at which these insights are implemented.
- Sustainable Value: Development of scalable data and AI platforms that demonstrate long-term viability and contribute to the company's competitive advantage.
- Team Performance: Achievement of team-specific objectives, professional development metrics, and retention rates of key talent.
- Data & AI Strategy (Expert): Ability to create and articulate a clear vision and strategic roadmap for data and AI, with a strong focus on business outcomes.
- Leadership & Team Building (Expert): Proven experience in leading and developing high-performing, multidisciplinary data and AI teams.
- Data Governance & Ethics (Expert): Deep understanding of data governance, data quality, privacy regulations (PDPA), and ethical AI principles.
- Business Acumen (Expert): Exceptional ability to connect data and AI capabilities to business value, revenue, and efficiency drivers.
- Machine Learning & AI Application (Advanced): Practical knowledge of deploying and scaling ML models to solve real-world business problems.
- Data Architecture & Platforms (Advanced): Strong knowledge of modern cloud data stacks, including data lakes, warehouses, and MLOps frameworks.
- Change & Value Advocacy: Expert: Proven ability to drive organizational change by leveraging data insights to secure buy-in and demonstrate sustainable value to stakeholders.
- Financial Impact: High: Financial decisions are critical to achieving key financial objectives.
- Key External Contacts: Industry Experts and Partners.
- Key Internal Contacts: Board Engagement, Maxis Management Team (MMT), Head of Department, Chief Information Officer (CIO).
- Problem Solving: Extensive: Final decision-maker on significant communication issues.
- Formal Education: Master’s degree in Computer Science, Data Science, AI, or a related field. A Ph.D. is preferred.
- Language: English
- Relevant Working Experience: Minimum 15 years of total work experience with at least 8 years in a senior leadership role within data and AI domains.
What’s next?
- Once you’ve applied online, our team will carefully review your application. Due to a high volume of applications, we appreciate your patience to allow for a fair and timely review process.
- Should you be shortlisted for the role, we will send you an invitation via email for a digital interview. You can also check on your application status by logging into your candidate account.
Maxis values diverse voices & people. We hire and reward our employees based on capability & performance — regardless of ethnicity, gender, age, education, religion, nationality or physical ability.
Skills Required
- Master's degree in Computer Science, Data Science, AI, or related field
- Ph.D. in relevant field
- Minimum 15 years total work experience with at least 8 years in senior leadership within data and AI domains
- Proven experience creating and executing data and AI strategy tied to business outcomes
- Proven leadership building and managing multidisciplinary data science, engineering, and analytics teams
- Deep understanding of data governance, data quality, privacy regulations (PDPA), and ethical AI practices
- Practical experience deploying and scaling ML models and MLOps frameworks in production
- Strong knowledge of modern cloud data stacks, data lakes, data warehouses and cloud platforms (GCP/AWS)
- Experience managing budgets and demonstrating measurable financial impact from data/AI initiatives
- Fluency in English
- Relevant certifications (e.g., Google Professional Data Engineer, AWS Certified Machine Learning)
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The Company
What We Do
Maxine is an award-winning nonfiction film and television studio founded by Mary Robertson, dedicated to creating journalist-and-filmmaker-driven nonfiction work.






