Data Scientist Lead

Changi Airport Group (Singapore) Pte. Ltd.; Singapore; On-site; SGD 180,000 - 280,000; Full time

Job summary

Changi Airport Group (Singapore) Pte. Ltd. is seeking an experienced Lead to shape data and AI product strategy, delivering scalable solutions for airport operations and business functions.

You will bridge operations and technology with stakeholders and lead a team of data scientists and engineers to build predictive models and data-driven insights. You will collaborate across product, engineering and business units, leverage existing data lakes, and drive end-to-end delivery from concept to

Qualifications

• 10+ years in data science roles, with 3+ years leading a team
• Degree in Data Science, CS, Statistics or related field
• Strong knowledge of ML methods: regression, classification, clustering, time series, anomaly detection
• Proficient in Python (and/or R) and ML libraries like scikit-learn, XGBoost, TensorFlow, PyTorch
• Solid data wrangling, EDA, feature engineering, model evaluation, business metrics
• Familiarity with MLOps including deployment, monitoring, versioning (MLflow, Airflow, CI/CD)
• Experience with Git and collaboration tools (GitHub/GitLab)
• Experience with data visualization tools (Tableau/Power BI)
• Excellent problem solving and communication skills
• Awareness of data governance, privacy, and security (GDPR, PDPA)

Responsibilities

• Collaborate across product, data engineers, and partners through all development stages
• Collect, process, and analyze large datasets from multiple sources
• Design, build, validate ML models and statistical algorithms
• Conduct exploratory data analysis to uncover insights and trends
• Define data requirements and objectives with stakeholders
• Communicate findings to non-technical stakeholders

Skills

Leadership

Data science

Python

Communication

Problem solving

Stakeholder management

Storytelling

Attention to detail

Business context

Education

Bachelor's or Master's in Data Science/CS/Statistics

Tools

scikit-learn

XGBoost

TensorFlow

PyTorch

Tableau

Power BI

Git

GitHub

Airflow

MLflow

CI/CD

Job description

We are looking for an experienced Lead to drive the strategic development and delivery of data and AI products that power intelligent decisions across airport operations and business functions. Reporting to the Senior Vice President, Airport Operations Technology & Corporate IT, this role bridges operations and business needs with technical solutions—providing technical strategies, stakeholder engagement, and team leadership to design and develop reusable, scalable, and cost-effective data and AI products to analyse complex data sets to identify trends, develop predictive models, and provide actionable insights for our airport operations and business. You will be expected to work as an individual and/or a team with stakeholders from various line of business units to understand operation and business needs and deliver data-driven solutions. You will collaborate with our existing data engineering team, cloud architect team and technology partners to leverage our current data lakes, data pipelines and data presentation layers to develop capabilities for the organisation. The candidate is expected to work in a fast-paced environment and participate in multiple projects.

Key Responsibilities:

• Collaborate with product owners, data engineers, and partners across all product development stages - from concept and design to prototyping, testing, data curation, deployment, industry scaling, and end-of-life.
• Collect, process, and analyse large data sets from various sources.
• Design, build, and validate machine learning models and statistical algorithms.
• Perform exploratory data analysis to uncover insights and trends.
• Collaborate with stakeholders to define data requirements and objectives.
• Communicate findings and recommendations to non-technical stakeholders.

Qualifications:

• At least 10 years of experience in a proven role as a data scientist or similar function, with at least 3 years in managing a team of data scientists, machine learning engineers and big data specialists
• Bachelor's or Master's degree in Data Science, Computer Science, Statistics, or a related field.
• Strong knowledge of statistical methods and machine learning techniques such as regression, classification, clustering, time series forecasting, and anomaly detection.
• Strong programming skills in Python (and/or R), with hands-on experience using machine learning libraries such as scikit-learn, XGBoost, TensorFlow, and PyTorch.
• Solid understanding of data wrangling, exploratory data analysis, feature engineering, and model evaluation, paired with the ability to select or define appropriate success metrics grounded in real business context.
• Familiarity with MLOps practices including model deployment, monitoring, and versioning of ML artifacts (e.g., MLflow, Airflow, integration with CI/CD pipelines).
• Experience using Git for version control and familiarity with common collaboration tools such as GitHub or GitLab.
• Experience with data visualization tools like Tableau or Power BI.
• Excellent problem-solving skills and attention to detail.
• Strong storytelling, communication and collaboration skills.
• Awareness of data governance, privacy, and security practices (e.g., GDPR, PDPA).