Principal Data Scientist (Data and AI)
- Singapore
- Permanent
- Full-time
- Design, develop and deploy AI/ML/Gen AI solutions in areas including SP's consumer utilities app, electric vehicle charging, grid planning and monitoring, asset optimization, billing operations, work site safety and customer experience.
- Provide ad-hoc decision support to business leaders through product analytics, experiment design, A/B testing and impact analysis.
- Engage business stakeholders to understand user requirements, leverage domain knowledge, drive project targets and deliver business value.
- Lead technical efforts to develop key AI/ML/Gen AI capabilities in areas such as time series forecasting, anomaly detection, graph network analysis, multimodal generative AI, autonomous agents, AI security guardrails, LLM evaluation framework and SLM fine-tuning.
- Work closely with data engineers, business analysts, product owners, UX designers, AI engineers and software engineers to adopt iterative, agile AI delivery framework.
- Establish and implement AI governance practices, including model documentation, validation, explainability, security guardrails, performance monitoring and ethical considerations.
- Promote AI literacy and democratization by building reusable tools, self-service analytics platforms, and conducting training and workshops for business users.
- Monitor and evaluate emerging AI tools, frameworks, and vendor solutions for internal adoption.
- Guide junior team members and manage interns/contractors.
- Minimum 5 years of experience in a data science role. This is a mid to senior level position with eventual career progression to team management.
- Proven track record of developing and deploying AI/ML solutions in cross-functional teams to solve business problems.
- Hands-on experience with Gen AI frameworks (e.g., LangChain, LlamaIndex, HuggingFace Transformers).
- Excellent understanding of machine learning, deep learning and generative AI models, their pros and cons, and ability to evaluate them for different applications.
- Extensive experience applying domain knowledge and statistical techniques in feature engineering to improve model performance and create innovative solutions.
- Deep proficiency in at least one of the following: CV, NLP, time series modeling, network analysis, predictive maintenance, document understanding, RAG, PEFT fine-tuning, Agentic AI.
- Able to actively engage stakeholders, navigate dynamic complexities, lead end-to-end project delivery and manage work of team members.
- Strong data visualization and storytelling skills, proficient in translating technical results to actionable business insights for business leaders.
- Experience deploying Gen AI models to production, including containerization (Docker), APIs, and cloud platforms (AWS, Azure, or GCP).
- Familiarity with governance frameworks like Singapore's Model AI Governance Framework, EU AI Act, or NIST AI Risk Framework.
- Knowledge in energy tech or related domain.