Top Data Jobs in Singapore

This role involves providing technical support, implementing, and maintaining enterprise IT infrastructure, including troubleshooting, system upgrades, and supporting disaster recovery planning.

The Head of Data Discovery manages the bank's data discovery platform, ensuring data accessibility and compliance, while enabling analytics innovation across various business units.

The Data Scientist will develop AI-driven solutions for supply chain optimization, utilizing advanced analytics, machine learning, and statistical modeling to deliver business impact.

Lead development of personalization and recommendation systems using large-scale transactional data. Define model strategy, build and deploy scalable ML pipelines, run experiments to measure impact, mentor data scientists, and collaborate with Product and Engineering to drive customer engagement and transactions.

As a Senior Data Scientist, you'll design and implement advanced retrieval and ranking algorithms for GoFood and GoPay, enhancing user experience and business impact through innovative solutions.

The Data Scientist will support analytics projects, collaborate on predictive solutions, and assist in deploying machine learning models while engaging stakeholders across GlobalFoundries.

As a Transformation Consultant, you'll lead strategic projects, engage with clients, identify business opportunities, and support sales to enhance organizational capabilities.

Design, build, and optimize end-to-end data ingestion and ETL pipelines on AWS into governed data lake zones. Implement data quality frameworks, error handling, and metadata/catalog management. Use IaC (Terraform/AWS CDK), write tests, support UAT, produce runbooks/documentation, and participate in Agile delivery.

Oversee health, safety and environment (HSE) for data centre construction projects across multiple sites. Conduct daily site visits, audits, safety walks, report incidents and near-misses, manage contractor inductions, ensure corrective actions, prepare monthly safety assessment reports, and support project management to achieve zero incidents and compliance with client protocols.

Design, build, and deploy production-grade ML models (cross-sell, upsell, recommendation, LTV), automate model lifecycles with SageMaker, leverage LLMs for personalization and insight generation, run A/B tests, collaborate with product and engineering, and mentor junior data scientists to drive measurable revenue outcomes.

The Data Engineer will optimize data infrastructure, develop scalable ETL processes, establish data governance, and collaborate with data teams to ensure data accuracy and performance.

As a Data Engineer, you'll design and develop cloud-native data platforms, create scalable data pipelines, and support analytics and reporting across teams.

Serve as the post-sale technical and commercial lead to drive adoption and consumption of Salesforce Data Cloud & Agentforce. Build executive relationships, develop consumption and adoption plans, provide architecture and integration guidance, identify and mitigate risks, coordinate cross-functional teams, and evangelize use cases to accelerate value and ACV growth.

Lead end-to-end delivery of cybersecurity projects for data centres and critical facilities, managing schedules, budgets, risks, vendors, and stakeholder communications. Conduct and support TVRA and other security risk assessments, ensure security-by-design and compliance requirements are integrated into designs, and produce governance reports and presentations.

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.