Top Data Jobs in Singapore

The DDF Engineering Lead will oversee a team of data engineers and DevOps engineers, driving the delivery of data products and implementing DataOps practices. Responsibilities include collaborating with cross-functional teams, optimizing data pipelines, ensuring adherence to governance policies, and promoting data quality. This role requires significant technical leadership and stakeholder engagement to maximize data utilization for business value.

The Data Engineer role involves building optimal ETL processes, managing data pipelines, and designing scalable data platforms for analytics. Responsibilities include improving data governance, collaborating with business teams, and implementing DevOps for data projects.

The Data Steward Supervisor will oversee a data stewardship team, focusing on improving data quality and operational efficiency. Responsibilities include recruiting and training staff, monitoring performance, allocating resources, and ensuring productivity standards are met. The role is essential for maintaining accurate and validated data. This position requires excellent problem-solving skills and organizational abilities.

As a Senior Advisor Data Scientist, you'll collaborate with a team to develop AI and ML solutions across client devices. This role involves integrating AI applications, optimizing ML models, and translating business questions into data-driven insights. You will also work closely with engineering teams to ensure effective deployment of applications.

As a Senior Analytics Manager at Grab, you will lead analytics teams to deliver data-driven insights, evaluate key business/product ideas, collaborate with various teams to design experiments, and uphold standards in measurement and analysis. Your role involves directing teams, developing analytics tools, and enhancing product velocity through data innovation.

The Senior Data Scientist will analyze transactional data to identify fraudulent activities, develop and deploy scalable machine learning models for fraud detection, and collaborate with various teams to integrate fraud detection systems. The role involves conducting experiments, monitoring model performance, and contributing to innovation in payment fraud detection.

The Senior Data Scientist (Analytics) will support product teams by providing data-driven insights, designing experiments, identifying trends, analyzing data with statistical techniques, and collaborating with stakeholders to inform product decisions. Responsibilities include launching A/B tests, developing data pipelines, and creating data models to enhance product features and drive effective decision-making.

The Senior Data Scientist (Recommendation) at Grab will develop machine learning models to enhance consumer recommendation experiences, leveraging big data for insights and product improvements. Responsibilities include implementing algorithms, conducting A/B tests, and collaborating with stakeholders to visualize results.