Top Data Jobs in Singapore

Lead technical design, development, and deployment of data platforms, analytics, and AI solutions. Set architecture, standards, and governance; drive MLOps/DataOps practices, model governance, and integration (including robotics). Provide hands-on delivery, technical direction, and mentorship to ensure scalable, secure, and reusable AI capabilities.

Lead regional AFC/AML analytics capability: design, build, validate and deploy AML/fraud detection models; guide country analytics teams; ensure model governance, data suitability, and production readiness across stakeholders and regions.

Design, build, deploy and maintain AI/ML and Generative AI solutions for government agency clients. Responsibilities include stakeholder collaboration, data cleaning and feature engineering, model development (classification/regression/LLM-based), backend API and frontend interface development, monitoring of deployed models, and researching/employing modern LLM frameworks, vector DBs, and agent techniques.

Lead and deliver concurrent standard or complex client projects from concept to implementation, manage scope, budget, risks, issues, and stakeholder communications, act as single client contact, support pre-sales, and ensure successful handover to operations.

The role involves managing AI and data science projects, engaging stakeholders, and delivering data-driven solutions while leading a team and guiding junior members.

The Data Analytics Lead will work with senior leadership on strategic projects, focusing on high-impact analytics solutions and driving execution for tangible results.

Build, deploy, and iterate predictive models and real-time scoring pipelines using behavioral and clickstream data to improve lead quality and campaign optimization. Collaborate with marketing, media buying, and analytics teams to translate business needs into hypotheses, perform exploratory analysis, monitor model performance, and communicate statistically rigorous insights to non-technical stakeholders.

Lead ETL, data processing, and analysis to generate actionable market intelligence for maritime clients. Build forecasting models, maintain dashboards and reports, support commercial desks with real-time insights, and present findings to stakeholders.

Lead large-scale analytic projects focusing on driving business impact through strategic analysis and machine learning/NLP models in the financial sector.

Lead Line-2 oversight of enterprise AI and data risk governance. Develop and implement governance frameworks, policies and KRIs; perform independent reviews; serve as Data & AI Committee secretariat; coordinate regional adoption, training, regulator engagement, and provide risk reporting and remediation guidance to senior management and Board.

The role involves driving AI and Data governance strategies, collaborating across teams, assessing data and AI risks, and improving data quality initiatives within the bank.

The Assistant Data Analyst Manager will lead an analytics team, manage stakeholder relations, oversee Power BI projects, and contribute strategically to data initiatives.

As a Senior Data Scientist, you'll design datasets, conduct model pre-training, and collaborate with teams to develop LLM features for diverse users.

As a Lead Data Scientist, you will design and deploy search and recommendation algorithms, optimizing user experience for GoFood and GoPay systems, leveraging large-scale data and machine learning expertise.

Lead Data Scientist responsible for developing and deploying multilingual large language models, building datasets, and improving AI safety alignment.

As a Senior Data Scientist, you will develop and deploy advanced AI models in deep learning, focusing on computer vision, voice, and text processing. Responsibilities include model optimization, performance evaluation, and collaboration with engineering teams.

The Data Scientist will develop and deploy AI models for computer vision and text processing, enhancing business products at GoTo Financial. Responsibilities include model optimization, documentation, and collaboration between data science and engineering teams.

The Lead Data Scientist will develop multilingual AI models, focusing on dataset creation and model training, while collaborating with product and engineering teams for deployment.

The Lead Data Scientist will develop machine learning solutions for fraud detection, manage model creation, deployment, and collaborate to ensure business impact.

As a Data Engineer, you will develop and manage data pipelines, ensuring reliable data ingestion and delivery while optimizing for simplicity and performance.

Lead data-driven strategies for cross-border payments, manage BI and Data Engineering teams, and enhance business efficiency through data insights.

Design, build, test, deploy and support Xceptor-based automation solutions. Gather requirements, create documentation/training, integrate with systems, run testing (unit/SIT/UAT), troubleshoot production, and enable consultants through training and case repositories.

The Director of Data will lead a team of data engineers, manage the P&L of the Data practice, and ensure effective collaboration across teams to drive data solutions.

As a Python and Kubernetes Software Engineer, you will develop data analytics solutions using open source tools, collaborating with a distributed team.

Lead a team in developing scalable data solutions, mentor engineers, manage expectations, and contribute to code. Focus on high-quality software practices.