An empowering career at Singtel begins with a Hello. Our purpose, to Empower Every Generation, connects people to the possibilities they need to excel. Every “hello” at Singtel opens doors to new initiatives, growth, and BIG possibilities that takes your career to new heights. So, when you say hello to us, you are really empowered to say…“Hello BIG Possibilities”.

Be a Part of Something BIG! 

As a Senior Data Scientist, you will assume a key role in leading AI/ML initiatives in Credit Management – developing AI/ML models to assess default risk, forecast payment behaviors and enable proactive credit control strategies. You’ll work on optimizing credit limits using risk-based segmentation, behavioral scoring, and portfolio analytics to balance revenue growth with risk exposure. You work will directly support business objectives in financial risk mitigation, customer lifecycle management and sustainable revenue optimization.

As part of the AI & Data Analytics (AIDA) business unit, this role also offers unique opportunities to shape enterprise-wide AI/ML frameworks, standards, and best practices across Singtel Singapore. You will contribute to defining common ways of working, champion model governance and responsible AI practices, and collaborate with internal & external stakeholders to align AI solutions with business strategy and regulatory expectations.

Make An Impact By

• Lead Credit Risk Analytics Initiatives: Partner with stakeholders in Credit Management, Finance, and business operations to identify high-impact opportunities in credit management. Define problem statements related to default prediction, credit limit optimization, and risk-based segmentation, and deliver end-to-end AI/ML solutions—potentially including Generative AI and LLM applications—that align with strategic and regulatory objectives.
• Model Development & Operationalization: Design, build, and productionize predictive models for assessing creditworthiness, forecasting payment behaviors, and optimizing credit controls. Champion best practices in model deployment, performance monitoring, explainability, and integration into enterprise credit decision engines to ensure scalability and compliance.
• Customer Risk Profiling & Portfolio Insights: Leverage advanced analytics to analyze customer financial behavior, payment trends, and credit usage patterns. Develop risk-based segmentation and portfolio analytics to inform dynamic credit strategies, mitigate financial exposure, and support sustainable revenue optimization across the customer lifecycle.
• 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 5 years of relevant working experience.

• 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.
• Provide technical mentorship across multiple project streams, ensuring junior and mid-level data scientists are growing in capability and delivering high-quality output.
• Contribute to building a culture of knowledge sharing and continuous improvement within the data science team.

Are you ready to say hello to BIG Possibilities?

Take the leap with Singtel to unlock new opportunities and accelerate your growth. Apply now and start your empowering career!