Senior/Lead Data Scientist

Morgan McKinley; Singapore; On-site; SGD 120,000 - 190,000; Full time

Job summary

A leading telecommunications and digital services provider seeks a seasoned AI and data analytics leader to drive large-scale AI/ML programmes in a data-driven enterprise. You will translate business priorities into measurable outcomes, oversee end-to-end model development, and mentor a team of data scientists while ensuring governance and scalability.

Responsibilities include customer analytics, experimentation, and stakeholder collaboration to deliver tangible business impact through

Qualifications

• Bachelor's or postgraduate degree in Computer Science, Mathematics, Statistics, or a related discipline, with at least 5-8 years of relevant experience.
• Strong expertise in machine learning and statistical modelling, including regression, time-series forecasting, supervised learning, segmentation, clustering, experimentation, and causal inference.
• Hands-on experience with Generative AI and LLMs, including fine-tuning, evaluation, prompt engineering, red-teaming, and performance monitoring.
• Proficiency in Python, SQL, Spark, Hadoop/Hive, and Databricks, with data visualisation experience using tools such as Power BI.
• Familiarity with software engineering best practices, version control (GitHub, GitLab, Bitbucket), cloud platforms (AWS, Azure, GCP), and ML lifecycle tools such as MLflow and Airflow.
• Proven technical leadership, problem-solving, and stakeholder management skills, with the ability to communicate complex insights clearly to technical and non-technical audiences.
• Strong customer-centric mindset and ability to translate data science capabilities into tangible business value.

Responsibilities

• Lead AI & Data Science Initiatives: Drive large-scale AI/ML programmes, define strategic roadmaps, and translate business priorities into measurable outcomes, leveraging Generative AI and LLMs where relevant.
• Model Development & Deployment: Oversee end-to-end model development, productionisation, integration, monitoring, and continuous improvement, ensuring scalability, explainability, and governance.
• Customer Analytics & Personalisation: Analyse customer behavioural data to drive segmentation, propensity modelling, cross-selling, product targeting, and lifecycle marketing optimisation.
• Experimentation & Optimisation: Design and execute A/B testing, uplift modelling, and other experimentation methods to improve campaign effectiveness and business performance.
• Technical Leadership: Lead, mentor, and develop data scientists while establishing best practices for code quality, reproducibility, documentation, and model lifecycle management.
• Stakeholder Management: Partner with senior business stakeholders and external collaborators, translating complex analytical insights into actionable recommendations aligned with business objectives.

Skills

Machine learning

Statistical modelling

Segmentation

Clustering

Experimentation

Causal inference

Generative AI

LLMs

Python

SQL

Spark

Hadoop/Hive

Databricks

Power BI

AWS

Azure

GCP

MLflow

Airflow

Education

Bachelor's or postgraduate degree in Computer Science, Mathematics, Statistics, or a related discipline

Tools

Python

SQL

Spark

Hadoop/Hive

Databricks

Power BI

GitHub

GitLab

Bitbucket

AWS

Azure

GCP

MLflow

Airflow

Job description

A leading telecommunications and digital services provider is accelerating its AI and data analytics capabilities to deliver smarter customer experiences, optimise operations, and unlock new business opportunities. The organisation offers the opportunity to lead impactful AI initiatives at scale within a complex, data-driven enterprise.

Role & Responsibilities

• Lead AI & Data Science Initiatives: Drive large-scale AI/ML programmes, define strategic roadmaps, and translate business priorities into measurable outcomes, leveraging Generative AI and LLMs where relevant.
• Model Development & Deployment: Oversee end-to-end model development, productionisation, integration, monitoring, and continuous improvement, ensuring scalability, explainability, and governance.
• Customer Analytics & Personalisation: Analyse customer behavioural data to drive segmentation, propensity modelling, cross-selling, product targeting, and lifecycle marketing optimisation.
• Experimentation & Optimisation: Design and execute A/B testing, uplift modelling, and other experimentation methods to improve campaign effectiveness and business performance.
• Technical Leadership: Lead, mentor, and develop data scientists while establishing best practices for code quality, reproducibility, documentation, and model lifecycle management.
• Stakeholder Management: Partner with senior business stakeholders and external collaborators, translating complex analytical insights into actionable recommendations aligned with business objectives.

Job Requirements

• Bachelor's or postgraduate degree in Computer Science, Mathematics, Statistics, or a related discipline, with at least 5 - 8 years of relevant experience.
• Strong expertise in machine learning and statistical modelling, including regression, time-series forecasting, supervised learning, segmentation, clustering, experimentation, and causal inference.
• Hands-on experience with Generative AI and LLMs, including fine-tuning, evaluation, prompt engineering, red-teaming, and performance monitoring.
• Proficiency in Python, SQL, Spark, Hadoop/Hive, and Databricks, with data visualisation experience using tools such as Power BI.
• Familiarity with software engineering best practices, version control (GitHub, GitLab, Bitbucket), cloud platforms (AWS, Azure, GCP), and ML lifecycle tools such as MLflow and Airflow.
• Proven technical leadership, problem-solving, and stakeholder management skills, with the ability to communicate complex insights clearly to technical and non-technical audiences.
• Strong customer-centric mindset and ability to translate data science capabilities into tangible business value.