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Singtel

Data Scientist #AIDA

Singtel is hiring a Data Scientist #AIDA in Singapore, Singapore. Level rates it ; you can apply on Singtel.

Level's read on this job

  • Builds AI ●●●● is how Level rates this data scientist role: the job is building AI systems.
  • Tools and skills the posting cites include Llama, MLflow and Databricks.
  • Level classifies it as a mid-level role.
  • Level lists 496 other open roles at Singtel.

AI in this role

llamamlflowdatabricks
prompt-engineeringfine-tuning

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”.

As a 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 network anomaly detection, customer behavioral analysis, 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 Network, Enterprise, Sales, 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.
  • 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.

 

 

 

 

How we rate this

Data Scientist #AIDA at Singtel rates 86 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Prompt engineeringFine-tuningLlamaMLflowDatabricks

Also common in data scientist jobs at this level

Pay

Typical data scientist job
$167k

This posting doesn't list pay. Use the typical data scientist figure when pay comes up. See data scientist jobs

Questions you could be asked

  1. How do you structure and test a prompt to get consistent output from a language model?
  2. Walk me through fine-tuning a model: what data did you use, and how did you check the result?
  3. What are the limits of Llama that you've run into, and how did you work around them?
  4. What's a project where you used MLflow hands-on?
  5. Walk me through how you've used Databricks in your day-to-day work.

Adapt your resume

  • List these exact terms on your resume: Prompt engineering, Fine-tuning, Llama, MLflow, and Databricks. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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