About This Role
The Data Scientist will collaborate with multidisciplinary teams, business stakeholders, and external partners to apply advanced analytics, statistical methods, and machine learning techniques to address complex business challenges and support data-driven decision-making. The role involves translating business needs into analytical solutions, developing and evaluating statistical and machine learning models, and working with technical teams to operationalize these solutions within existing analytics platforms and production environments. These efforts will enhance STB's analytical capabilities and deepen understanding of visitors to support STB's strategic objectives and contribute to the growth of Singapore's tourism industry.
Responsibilities
- Translate complex business problems into well-defined data science objectives and determine appropriate statistical and machine learning approaches
- Design, develop, and implement statistical and machine learning models, applying advanced data science techniques where appropriate
- Develop and apply robust model validation and evaluation methods to assess model performance, accuracy, reliability, and limitations, ensuring models are fit for their intended purpose
- Perform data exploration, preprocessing, and feature engineering to prepare complex datasets for model development, training, and evaluation
- Collaborate with data engineers and relevant technical teams to integrate and deploy statistical and machine learning models into production environments, ensuring they meet operational and business requirements
- Monitor and evaluate model performance over time, identify potential performance degradation, and recommend appropriate enhancements, recalibration, or retraining to maintain model effectiveness
- Develop and maintain documentation covering model methodologies, assumptions, validation results, and operational requirements to support reproducibility, knowledge transfer, and ongoing maintenance
- Manage and take ownership of data science projects, ensuring deliverables meet agreed objectives, scope, quality standards, and timelines, while proactively managing risks, dependencies, and stakeholder expectations
- Collaborate with cross-functional teams, including data engineers, DevOps engineers, product managers, business analysts, and business stakeholders, to support the development, integration, and operationalization of data science solutions
- Collaborate with relevant teams and stakeholders to review and enhance existing data collection methods and strategies to better support data science and modeling requirements
- Evaluate new data sources, including the quality and suitability of datasets and labeled training data, to identify opportunities for enhancing existing data science capabilities
- Work with internal and external stakeholders to identify, source, and assemble complex datasets that meet the requirements of data science projects
