Application of Advanced Analytics and Data Science to Support Strategic Business ObjectivesTranslate complex business problems into well-defined data science objectives and determine appropriate statistical and machine learning approaches to address them.Design, develop and implement statistical and machine learning models to address business needs, 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 that models are fit for their intended purpose.Perform data exploration, preprocessing and feature engineering to prepare complex datasets for model development, training and evaluation.
We’re looking for a Data API Engineer to join our Data API Team and help improve the feature set, reliability and performance of our Data API, based on the PostgREST project.
Real-Time Data Pipeline Development: Build, maintain, and optimize end-to-end data ingestion pipelines for business logs, user behavior data, and database records.
Lead the end-to-end management of MS SQL Server, PostgreSQL and DuckDB (DuckLake) database systems, ensuring their stability, scalability and reliability.
You study Computer Science, Engineering (Computer/Telecommunication) or any related quantitative field with a prospect to complete in the near to mid-term future and excellent grades.
We are seeking an experienced Databricks Architect / Lead Data Engineer to lead the design, development, and delivery of enterprise-scale data platforms on Databricks and AWS.
Build and maintain customer lifetime value (LTV) models that inform commercial investment decisions across Singapore, Australia, Japan and Emerging Markets.
Design and implement quantitative analytical AI Agent and frameworks, including scalable predictive models, customer segmentation and advertising optimisation that improve business performance and customer engagement.