Senior Manager, AI & Data Science

POSITION SUMMARY:

This role involves delivering advanced AI solutions using state-of-the-art architectures such as LLMs, GANs, reinforcement learning, and deep learning. The Manager combines hands-on technical expertise with leadership responsibilities, ensuring AI models are designed, deployed, and maintained in line with business strategy. This role partners with IT and business stakeholders to align solutions with organizational needs, generate predictive and prescriptive insights for business-critical decision-making.

PRIMARY RESPONSIBILITIES:

• Lead end-to-end data science workflows, from data acquisition to deploying AI and ML models (e.g., LLMs, GANs, RL systems).
• Advancement of organizational capabilities in AI and data science.
• Oversees design, training, and deployment of advanced AI models including transformers, LLMs, GANs, and reinforcement learning systems.
• Implement MLOps practices for model lifecycle management, ensuring scalable and drives positive business impacts.
• Work with IT and business to embed AI/ML solutions and predictive analytics into key decision-making processes.
• Ensure compliance with data governance, intellectual property, and regulatory standards
• Ability to communicate advanced analytics topics, such as model interpretability, to both technical and non-technical leaders and facilitate data-driven decision making.
• Mentor and lead teams of data scientists and ML engineers, building capacity for advanced analytics and AI excellence.

KEY PERFORMANCE INDICATORS:
1. Execution of AI and analytics roadmap.
2. Successful deployment and adoption of advanced analytics, AI/ML applications and LLM-powered solutions across business units
3. Advancement of organizational capabilities in AI and analytics.
4. Adoption of predictive and prescriptive models in decision-making workflows
5. Influence of insights on strategic business decision-making.
6. Growth and development of the data science team.
7. Good interpersonal skills, insightful communication and collaboration with stakeholders
8. Adherence to data privacy, compliance, and ethical standards in data science and AI.
9. Ability to manage projects and complete tasks in a timely and effective manner.
10. Develops and maintains constructive relationships with internal and external customers
QUALIFICATIONS:
Experience

• Currently worked at a company or institution heavily involved in data science or AI projects
• Experience in data science, machine learning, or AI/ML development
• Proven record of leading a high-performing technical team and guide enterprise transformation
• Proven track record of delivering advanced analytics and AI solutions that drive measurable business outcomes
• Experience leading cross-functional teams, managing complex data initiatives, and aligning technical efforts with strategic business goals
• Exposure to collaborative environments involving external partners, clients, or teams

Education

• Degree in Data Science, Artificial Intelligence, Computer Science, Statistics, Mathematics, Engineering, or a related quantitative discipline
• Preference is given to candidates with a post graduate degree from a major, accredited institution

Skills / Competencies

• Lead high-performing technical teams and guide enterprise transformation.
• Advanced knowledge of transformers, LLM orchestration, reinforcement learning, and generative modeling.
• Expertise in programming and technical skills on data science and AI technologies, such as machine learning, deep learning, NLP, LLM and predictive modeling.
• Expertise in distributed training and large-scale experimentation.
• Strong background in time-series, forecasting, and optimization models.
• Familiarity with enterprise data ecosystems and large-scale pipelines.
• Strong knowledge of scalable MLOps, model deployment and lifecycle management
• Ability to deliver AI projects with strategic business impact.
• Strong problem-solving abilities and advanced proficiency in data analysis and interpretation.
• Skilled in project management and stakeholder engagement
• Good communication and collaboration skills across technical and business domains.
• Excellent leadership and team management skills.
• Ability to adapt to a fast-paced, multicultural dynamic environment.
• Fluency in English, Cantonese, and Mandarin.