Top Data Jobs in Singapore

The role involves developing AI-driven solutions for semiconductor engineering, focusing on GenAI systems, data pipelines, and machine learning models while collaborating with cross-functional teams.

The Principal Data Scientist will optimize semiconductor yields, develop data pipelines, apply advanced analytics, support experimentation, and communicate findings effectively.

As a Data Scientist, you will optimize semiconductor manufacturing processes through data analysis, develop predictive models, and automate data workflows.

Serve as ASOs single front door for Operations demands across Asia, translating business needs into prioritized initiatives, managing demand pipeline, shaping improvement using AI/data/APIs, and coordinating stakeholders to deliver operational efficiency, compliance, and value realization.

Assist in building and maintaining data ingestion pipelines and storage for AI workflows. Implement deployment, security, and monitoring for applications; collaborate with stakeholders and design teams; test and validate data verification and AI workflows; document solutions and follow best practices while continuously learning new tools.

Lead and mentor a logistics analytics team to deliver insights on fleet performance, delivery efficiency, and cost optimization. Shape analytics roadmap, design performance metrics and AI data products, apply decision science and operations research, manage end-to-end analytics execution, and present executive-ready recommendations to drive measurable improvements.

Collect, analyze, and interpret game data to produce insights for R&D, marketing, and operations; build scalable data pipelines and ML models; collaborate with product managers and engineers; research new ML/AIGC approaches for gaming applications.

Build and productionize ML systems for personalization, search, and recommendations. Apply statistical and ML models using Python and SQL, collaborate with stakeholders, and measure business impact across cloud environments.

Analyze large datasets to identify trends and deliver actionable insights; design and monitor KPIs; build and maintain dashboards and reporting frameworks; conduct ad hoc analyses; ensure data quality and support reporting infrastructure in partnership with product and business teams.

Support the Data Science team to design, develop, deploy, and maintain analytics and ML solutions for manufacturing. Responsibilities include data collection/cleansing, EDA, predictive modeling, stakeholder collaboration, production deployment support, and presenting results to leadership.

Lead strategic APAC accounts to drive retention and growth: execute account plans, collaborate with sales and operations, monitor KPIs, support renewals/pricing, resolve client issues, and improve account management processes.

Design, build, and maintain scalable data pipelines, data lakes, and databases; ingest and map customer financial datasets; monitor pipeline reliability; translate business requirements into data flows and analytical insights to ensure high-quality, usable data.

Operate, maintain, and optimize hybrid cloud Data and AI platforms (Cloudera CDP/CML, Hadoop, Spark) across AWS and on-prem. Perform platform upgrades, security patching, container/Kubernetes/OpenShift administration, monitoring, troubleshooting, and automation using Shell/Python. Collaborate with Infrastructure, Security, SRE, and Data/ML teams to ensure availability and scalability of AI/ML and Generative AI services (SageMaker, EMR, Bedrock).

Lead functional business analysis for enterprise KYC/AML capabilities across Group Technology & Ops. Manage stakeholder relationships, define capabilities, translate business requirements into functional and non-functional requirements, oversee testing and scope control, support deployments and post-go-live knowledge transfer, and lead and develop a team of functional business analysts.

Operate and maintain Tencent's overseas big-data platforms for platform and cluster stability; troubleshoot platform/component errors and performance issues; assist users; optimize workflows, costs, and architectures; and develop operational tools for capacity management, DevOps, automation, coverage analytics, and health monitoring.

Support the AI team to build generative AI and computer vision solutions: code in Python, explore and analyze datasets, identify patterns, report findings, and implement models using PyTorch, TensorFlow, scikit-learn, and pandas.

Analyze casino operations and product performance, build models and ML solutions for floor optimization, demand forecasting and manpower scheduling, create dashboards and A/B tests, collaborate with Operations, Marketing, BI, and IT to translate analytics into business strategy and operational improvements.

Abstract and enter clinical data from health records, ensure data quality and confidentiality, use EHR/practice management systems and Microsoft Office, troubleshoot basic access/VPN/MFA issues, and collaborate with clinical teams to support operations.

Analyze payment flows and network fees, translate network specifications into billing models, identify cost-saving opportunities, partner with engineering, product, and finance, maintain fee accuracy and alerts, document and scale operational processes, and educate stakeholders.

Lead and coordinate health, safety and wellbeing activities for office and data centre construction projects. Monitor compliance, record incidents, perform risk assessments/audits, support legal compliance reviews, train staff, and support global H&S campaigns.

Lead a cross-functional AI/ML team to define strategy, design and deploy scalable production AI solutions (Generative AI, NLP, vision, time-series), drive research, ensure code quality and CI/CD, mentor engineers, and collaborate with business partners to deliver impactful decision-science products.

Design, build, and maintain production ML models and AI products focused on personalization, recommendation, propensity scoring, and Next Best Action. Collaborate with engineers, analysts, and stakeholders to deliver measurable player engagement outcomes, integrate models into pipelines, and expand AI capabilities across titles.

Design, develop, deploy, and monitor ML and deep learning solutions including Generative AI and transformer models. Build end-to-end MLOps pipelines, use LLMs, embeddings, vector DBs, and collaborate with data engineering and stakeholders to deliver production AI products and mentor junior staff.

Analyze PB-scale trading, transactional, operational and customer data; build visualizations, ML models and experiments; translate findings into actionable recommendations for trading, operations, product and executives in a fast-paced environment.

Perform radar data processing, quality control, and derive rainfall rates; research radar reflectivity–rainfall relationships; integrate radar into data assimilation systems; write reports and publications; perform related administrative and fieldwork tasks.