Data Scientist - Tourism Analytics

About the role

The Data Scientist works with multidisciplinary teams, business stakeholders and external partners to apply advanced analytics, statistical methods and machine learning to complex business challenges. The role turns business needs into analytical solutions, develops and evaluates statistical and machine learning models, and works with technical teams to put them into production. It aims to strengthen the organisation's analytical capabilities and deepen understanding of visitors to support its strategic objectives and the growth of Singapore's tourism industry.

Key responsibilities

• Translate complex business problems into data science objectives and choose appropriate statistical and machine learning approaches.
• Design, develop and implement statistical and machine learning models, with robust validation and evaluation of performance, accuracy and reliability.
• Perform data exploration, preprocessing and feature engineering on complex datasets.
• Work with data engineers and other technical teams to deploy models into production, monitor performance over time and recommend recalibration or retraining.
• Maintain documentation on model methodology, assumptions, validation results and operational requirements.
• Own data science projects end-to-end, managing scope, quality, timelines, risks and stakeholder expectations.
• Collaborate with data engineers, DevOps engineers, product managers, business analysts and stakeholders on solution development and integration.
• Review and improve data collection methods, evaluate new data sources and source complex datasets internally and externally.
• Contribute to the design of integrated data models using structured and unstructured datasets.

Required profile

• At least 3-5 years of experience developing, evaluating and implementing statistical and machine learning models for real-world business problems.
• Ability to manage data science projects independently and deliver quality outcomes within agreed scope and timelines.
• Strong project management, analytical, critical thinking and problem-solving skills.
• Good command of written and spoken English.

Required skills

• Quantitative and statistical modelling; experience with structured and unstructured datasets and data preprocessing.
• Proficiency in Python for statistical modelling and machine learning, and SQL for data extraction, manipulation and querying.
• Advantageous: cloud-based data science platforms such as AWS, and MLOps practices including model deployment, monitoring and lifecycle management.