Key Responsibilities:
Hands-on AI Delivery
- Lead and contribute directly to the design, development, and deployment of AI/ML solutions across Singtel Consumer, Enterprise, Network, IT, and Corporate domains.
- Translate complex business problems into well-scoped AI use cases with clear success metrics and measurable impact.
- Drive end-to-end AI/ML lifecycle ownership: problem framing, data strategy, feature engineering, model development, evaluation, deployment, and post-launch monitoring.
- Apply a broad range of techniques including machine learning, data science, optimisation, and GenAI where it delivers real value.
- Improve and modernise existing AI solutions, enhancing accuracy, scalability, robustness, and maintainability.
- Make pragmatic technical and architectural decisions, balancing speed, quality, and long-term sustainability.
- Lead selected GenAI and LLM-enabled use cases, including but not limited to RAG, agentic workflows, and AI-assisted decisioning.
- Work closely with platform and governance teams to ensure GenAI solutions are secure, responsible, and production-ready.
- Stay abreast of emerging AI trends and evaluate their applicability to Singtel's business.
People Leadership
- Lead, mentor, and develop a team experienced data scientists.
- Act as a technical role model and coach, providing hands-on guidance and constructive challenge.
- Foster a strong team culture focused on engineering quality, business impact, and continuous learning.
- Support hiring, performance development, and talent growth within the team.
Stakeholder & Partner Engagement
- Partnerclosely with business stakeholders to shape AI roadmaps and prioritisehigh-value use cases.
- Collaboratewith leading AI ecosystem partners such as OpenAI, Databricks, Mistral, NVIDIAand others.
- Represent Singtel at industry forums, conferences, and partner engagements, contributing to thought leadership and external visibility where appropriate.
Skills for Success:
- Bachelor or Postgraduatedegree in computer science, mathematics, statistics, or a related field.
- 15+ years of experience in AI/ machine learning / data science, with a strong track record of hands-ondelivery.
- Experience leading AIinitiatives from ideation through production in complex, real-worldenvironments.
- Prior experience mentoring ormanaging technical teams is required.
- Experience in largeenterprises, telco, tech, financial services, or consulting environments isadvantageous.
- Deep technical and datascience expertise, demonstrating proficiency in:
- Machine Learning &Statistical Modelling: Including linear regression, GLMs, time seriesforecasting, supervised learning (e.g., gradient boosted trees, neuralnetworks), segmentation, clustering, design of experiments, and causalinference.
- LLMs & Generative AI:Fine-tuning and evaluation of large language models (e.g., GPT, LLaMA), promptengineering, red-teaming, and performance monitoring
- Efficient data manipulation(with skills in SQL, Python, Spark, Hadoop/Hive, and Databricks) and datavisualization (using tools like Power BI).
- Familiar with softwareengineering best practices, including modular code design, reproducibility, andtesting. Proficient with version control tools such as GitHub, GitLab, andBitbucket
- Exposure to cloud platforms(e.g., Azure AWS, GCP) and ML lifecycle tools (e.g., MLflow, Airflow)
- Ability to review code,designs, and models, and to contribute hands-on is required.
