Senior Data Scientist, Enterprise AI #AIDA
Singtel is hiring a Senior Data Scientist, Enterprise AI #AIDA in Singapore, Singapore. Level rates it ; you can apply on Singtel.
Level's read on this job
- On Level's scale, this data scientist role is Builds AI ●●●●: the job is building AI systems.
- The posting mentions Llama, MLflow and Databricks among its tools and skills.
- Level classes it as a senior role.
- Singtel has 496 other open roles on Level.
- Posted within the past two weeks.
AI in this role
Powering the Future with AIDA
To lead the next phase of our AI evolution, we’ve launched a new business unit AIDA – Artificial Intelligence & Data Analytics – a strategic engine driving our transformation designed to scale our AI ambitions with precision and purpose. This marks a pivotal shift in how we operate, innovate, and serve to embed intelligence into every layer of our business.
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
You will work closely with cross-functional stakeholders (e.g. Network, Finance, Enterprise Business, Product, and Operations) to translate complex business challenges into scalable AI solutions, leveraging advanced machine learning, optimization techniques, and Generative AI where applicable.
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.
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.
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!
How we rate this
Senior Data Scientist, Enterprise AI #AIDA at Singtel rates 88 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.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ 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
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
- How do you structure and test a prompt to get consistent output from a language model?
- Walk me through fine-tuning a model: what data did you use, and how did you check the result?
- What are the limits of Llama that you've run into, and how did you work around them?
- What's a project where you used MLflow hands-on?
- 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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