Lead Data Scientist

About the Role

We are seeking a seasoned Lead Data Scientist to spearhead the strategic creation and deployment of advanced data and AI solutions that support intelligent decision-making across airport operations and business functions. Reporting directly to the Senior Vice President of Airport Operations Technology & Corporate IT, this role serves as a crucial connector between operational and business requirements and technical execution. You will guide technical strategies, foster stakeholder collaboration, and lead teams in designing and implementing reusable, scalable, and cost-efficient data and AI products that analyze complex datasets to detect trends, build predictive models, and deliver actionable insights.

The ideal candidate will work independently and collaboratively with stakeholders from diverse business units to understand operational and business challenges, producing data-driven solutions. Collaboration with existing data engineering, cloud architecture teams, and technology partners is essential to leverage current data lakes, pipelines, and presentation layers to enhance organizational capabilities. This position demands adaptability in a fast-paced environment and managing multiple projects concurrently.

Key Responsibilities

• Partner with product owners, data engineers, and cross-functional partners throughout all phases of product development—from conceptualization and design to prototyping, testing, data management, deployment, scaling, and retirement.
• Aggregate, cleanse, and analyze large volumes of data from multiple sources.
• Develop, validate, and maintain machine learning models and statistical algorithms.
• Conduct exploratory data analysis to reveal patterns and insights.
• Work closely with stakeholders to capture precise data requirements and objectives.
• Effectively present analytical findings and strategic recommendations to non-technical audiences.

Qualifications and Experience

• Minimum 10 years of experience in data science or related fields, including at least 3 years in leadership overseeing data scientists, machine learning engineers, and big data professionals.
• Bachelor's or Master's degree in Data Science, Computer Science, Statistics, or a related discipline.
• Expertise in statistical methodologies and machine learning techniques encompassing regression, classification, clustering, time series forecasting, and anomaly detection.
• Proficient in programming with Python and/or R, and experienced with machine learning frameworks such as scikit-learn, XGBoost, TensorFlow, and PyTorch.
• Strong skills in data wrangling, exploratory data analysis, feature engineering, model validation, and selecting relevant success metrics tied to business goals.
• Knowledgeable about MLOps frameworks including model deployment, monitoring, and version control (using tools like MLflow, Airflow, and integrating with CI/CD pipelines).
• Experience with Git version control and collaboration platforms such as GitHub or GitLab.
• Familiarity with data visualization software such as Tableau or Power BI.
• Excellent analytical problem-solving abilities and meticulous attention to detail.
• Ability to communicate complex data concepts through compelling storytelling and foster collaborative teamwork.
• Understanding of data governance, security, and privacy regulations (e.g., GDPR, PDPA).