Senior Data Scientist, Enterprise AI #AIDA
Indexed description
At Singtel, this is more than a technology upgrade. It’s a strategic transformation that redefines how value is created across the enterprise core—augmenting human capabilities and unlocking entirely new potential. It is a transformation journey by aligning people, platforms, and processes under one cohesive strategy. Our mission is to build AI literacy and foster a culture where intelligence empowers people.
We welcome you to join us on a transformational journey that’s reshaping the telecommunications industry — and redefining what’s possible with AI at its core. Grow with us in a workplace that champions innovation, embraces agility, and puts human potential at the heart of everything we do.
Be a Part of Something BIG!
As a Senior Data Scientist within the AI & Data Analytics (AIDA) business unit, you will play a critical role in designing and deploying enterprise-scale AI solutions that drive intelligent decision-making across Singtel’s business domains.
This role goes beyond traditional analytics to focus on high-impact AI use cases, including pricing optimization, anomaly detection, and predictive intelligence across network, customer, and operational environments.
You will develop and operationalize advanced AI/ML models and simulation frameworks to:
- Optimize pricing strategies and revenue outcomes
- Detect anomalies and risks in real time across large-scale data systems
- Enable proactive, automated decisioning across enterprise workflows
Make An Impact By
- Lead Data Science Initiatives: Drive end-to-end AI programs focused on enterprise use cases, including pricing optimization, anomaly detection, and forecasting. Partner with business and technical stakeholders to define problem statements and architect scalable AI-driven solutions aligned with strategic priorities.
- AI Solution Development & Integration: Build and productionize scalable AI pipelines and decision systems, integrating models into enterprise platforms and workflows. Ensure robustness in model governance, explainability, monitoring, and lifecycle management.
- Cross-Domain Data & Insight Generation: Leverage diverse datasets (network, customer, financial, operational) to uncover insights and enable:
- Root cause analysis via anomaly detection
- Scenario testing via digital twins
- Optimization of business levers such as pricing, capacity, and resource allocation
- Data Exploration & Experimentation: Enable robust data exploration, insight discovery, and experimentation for lifecycle marketing campaigns. Devise and execute rigorous A/B tests, segmentations, and optimization strategies to continuously improve business outcomes.
- Technical Mentorship & Code Quality: Provide guidance to junior data scientists and collaborate on code reviews to ensure adherence to best practices, maintain high code quality, and promote knowledge sharing within the team.
- Bachelor or Postgraduate degree in computer science, mathematics, statistics, or a related field, with at least 3 years of relevant working experience.
- Telecom or Insurance industries Sales / Marketing analytics experience will be an advantage.
- Deep technical and data science expertise, demonstrating proficiency in:
- Machine Learning & Statistical Modelling: Including linear regression, GLMs, time series forecasting, supervised learning (e.g., gradient boosted trees, neural networks), segmentation, clustering, design of experiments, and causal inference.
- LLMs & Generative AI: Fine-tuning and evaluation of large language models (e.g., GPT, LLaMA), prompt engineering, red-teaming, and performance monitoring
- Efficient data manipulation (with skills in SQL, Python, Spark, Hadoop/Hive, and Databricks) and data visualization (using tools like Power BI).
- Familiar with software engineering best practices, including modular code design, reproducibility, and testing. Proficient with version control tools such as GitHub, GitLab, and Bitbucket
- Exposure to cloud platforms (e.g., Azure AWS, GCP) and ML lifecycle tools (e.g., MLflow, Airflow)
- Strong problem-solving skills, with the ability to identify and solve complex business problems through data analysis.
- A team player with a customer-focused mindset, able to work well in a team and passionate about delivering exceptional customer experiences.
- Excellent data visualization and communication skills, with the ability to present insights and findings in a clear, concise, and compelling manner, both in written and verbal form.
- Experience in mentoring junior team members through collaborative problem solving, pair programming, and constructive code reviews.
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