Senior Data Scientist, Marketing AI

Be a Part of Something BIG!

As a Senior Data Scientist within the AI & Data Analytics (AIDA) business unit, you will assume a key role in driving insights discovery and AI/ML model development to predict and respond to market changes and their impact on Singtel’s business.

Your work will influence critical decisions across the organization—enabling data-driven strategies that uncover new customer insights, optimize operations, and unlock new revenue streams.

In this role, you will play a leading part in advancing AI initiatives, where AI is used to personalize and scale telco product and service offerings. You will develop predictive models for customer eligibility, churn/purchase propensity, and cross-sell optimization. This includes close collaboration with internal stakeholders and external partners to co-create data-driven AI/ML solutions.

Make an impact by

• Lead Data Science Initiatives: Drive AI/ML initiatives supporting Singtel’s product and service offerings by working closely with stakeholders from Marketing, Product, and external partners. Define problem statements and architect end-to-end solutions—including the use of Generative AI and LLMs where applicable—to align with strategic objectives, regulatory requirements, and partner needs.
• Model Development & Integration: Design, build, and productionize analytical models that enable intelligent decisioning within customer journeys. Integrate these models into customer-centric decision engines while championing best practices around model governance, scalability, explainability, and continuous performance monitoring.
• Customer Behavior & Lifecycle Analysis: Leverage customer behavioral data across Singtel’s Mobile, Broadband, and entertainment services to uncover actionable insights. Maintain and enhance analytical models that inform segmentation, product targeting, and value-based engagement strategies. Enable data exploration, insight discovery, and controlled experimentation (e.g., A/B testing, uplift modeling) to support lifecycle marketing and campaign optimization.
• 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.
• Stakeholder Communication: Communicate complex analytical findings and recommendations to diverse audiences—ranging from technical teams to senior leadership—in a clear, concise, and compelling manner.

Skills for Success

• 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:

a) 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.

b) LLMs & Generative AI: Fine-tuning and evaluation of large language models (e.g., GPT, LLaMA), prompt engineering, red-teaming, and performance monitoring

c) Efficient data manipulation (with skills in SQL, Python, Spark, Hadoop/Hive, and Databricks) and data visualization (using tools like Power BI).

d) 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.