Director, AI & Data Science

POSITION SUMMARY:

Provide visionary leadership for the company’s AI strategy and oversees development of advanced AI systems. The Director is accountable for defining the AI roadmap, ensuring delivery of high-impact solutions using architectures such as LLMs, GANs, reinforcement learning, and deep neural networks; accountable for building high-performing teams, scaling predictive pipelines, and driving technical innovation that provides reliable foresight and actionable intelligence.

PRIMARY RESPONSIBILITIES:

• Set the strategic direction for data science and AI initiatives by aligning them closely with the organization's business objectives and growth strategies.
• Drive the end-to-end data science process, starting from business understanding, data engineering, modeling, validation, and the deployment of AI-powered solutions into production environments.
• Oversee the design, development, and deployment of advanced data science, AI models and algorithms for predictive analytics, machine learning, and deep learning applications, ensuring solutions are robust, scalable, and ethical.
• Lead design and deployment of advanced models including transformers, LLMs, GANs, VAEs, and reinforcement learning.
• Develop and deploy predictive and statistical models to extract insights from structured/unstructured datasets.
• Ensure insights derived from AI pipelines are scalable, explainable, and reliable.
• Champion best practices in AI lifecycle management, including model monitoring, retraining and MLOps to guarantee long-term success and reliability of deployed solutions.
• Communicate complex analytic concepts and results to non-technical audiences, including executive leadership, to facilitate data-driven decision making.
• Recruit, lead, mentor, and develop a diverse team of data scientists and AI professionals

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. Enterprise adoption and reliability of predictive insight platforms.
4. Advancement of organizational capabilities in AI and analytics.
5. Measurable impact of insights on strategic decision-making.
6. Growth and develop of the data science team.
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, including a combination of industry roles, applied research, or high-impact project work
• 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
• Experience contributing to cross-functional projects involving IT and business teams.
• Exposure to collaborative environments involving external partners, clients, or interdisciplinary teams

Education

• A 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.
• Ability to deliver optimization and AI projects with significant strategic impact through effective project management, stakeholder engagement, and leadership of multidisciplinary teams.
• Strong decision analytics skills
• Strong communication skills to explain complex information to both technical and non-technical audiences;
• Extensive hands-on experience with programming knowledge across data science, machine learning, deep learning, NLP, predictive modeling, and AI deployment.
• Highly skilled in advanced data analysis, interpretation, feature engineering, hyperparameter optimization, time-series analysis, forecasting, and comprehensive problem-solving.
• Demonstrated expertise in transformer models, LLM fine-tuning, GANs, VAEs, reinforcement learning, and simulation modeling.
• Proficient in designing and managing enterprise data ecosystems, scalable pipelines, MLOps frameworks, and implementing decision intelligence
• Excellent leadership and team management skills.
• Fluent in English, Cantonese, and Mandarin
• Ability to work and demonstrate good leadership in fast-paced, multicultural environments