Top Data Jobs in Singapore

Design and deploy computer vision and deep learning solutions for manufacturing inspection and monitoring. Extract and clean large datasets, build multimodal AI models, apply MLOps for production deployment, and collaborate with cross-functional teams to translate research into operational systems and documentation.

Apply data science and ML to semiconductor yield and process optimization: build data pipelines, analyze sensor and tool logs, support DOE, develop models, and create dashboards to guide engineering improvements.

Design and lead end-to-end enterprise data and GenAI architectures, drive cloud migration/modernization, define GenAI/Copilot/agentic patterns (RAG, embeddings, vector search), establish MLOps/LLMOps and governance, ensure Responsible AI and security, and act as trusted technical advisor across presales through production.

Design, build, and maintain scalable data pipelines, data models, feature stores, and data catalogues to support AI model training and inference. Ensure data quality, lineage, governance, and secure integration of diverse real-time and batch transport data sources. Collaborate with AI architects, infrastructure engineers, and stakeholders to deliver production-grade data products and maintain pipeline reliability.

Lead the design and delivery of enterprise-scale data platforms and pipelines, using modern data platforms, processing frameworks, streaming technologies, and cloud services. Build, lead, and mentor a data engineering team; support client relationships, proposals, migrations, governance, security, and compliance. Contribute technical thought leadership through blogs and community engagement while delivering solutions from proof of concept through commercialization.

Lead the APAC Solutions Consulting team in a player-coach role, recruiting and mentoring consultants while owning technical strategy for strategic accounts. Partner with sales, professional services, product, and engineering teams to accelerate deals, improve technical win rates, and support customer retention. Build scalable processes, advise executive stakeholders, and lead complex solutions from presales through implementation. The role is remote in Singapore or China and requires approximately 25% travel.

Manages and expands public-sector client accounts by building relationships, ensuring satisfaction, reducing churn, and driving revenue and margin growth. Develops account strategies, identifies opportunities, coordinates global stakeholders and partners, supports clients throughout the buying lifecycle, and manages pipelines, forecasts, and quotas in Salesforce.com. Serves as the primary client contact, resolves issues, and translates business needs into tailored technology solutions.

Develop and maintain end-to-end Xceptor data automation and integration solutions for banking and capital markets workflows. Configure MessageHub channels, Mail integrations, and REST/SOAP APIs; build parsing, routing, transformation, reconciliation, validation, and exception-handling rules; integrate financial platforms; troubleshoot production workflows; optimize performance; and collaborate with architects, analysts, and market specialists.

Lead global initiatives to improve facilities cost data visibility, metrics alignment, reporting, and process enablement. Drive data governance, reporting development, and sustainable reporting operations across Global Facilities to improve decision-making and business insight.

Document existing Excel reports and workflows, identify automation opportunities, and support solutions using Excel, Power BI, Power Automate, VBA, and APIs. Analyze data for trends and anomalies, ensure accuracy, maintain process documentation, and create reports, dashboards, and presentations that communicate insights to senior management.

As a Data Scientist, you will analyze large datasets, develop predictive models, and improve existing tools while collaborating with teams for data analysis projects.

The IT Engineer (Data Services) is responsible for managing and optimizing database systems, ensuring data availability, performance, and compliance, while also developing automated solutions and collaborating with site customers.

Leverages AI, machine learning, predictive analytics, optimization, and data visualization to support strategic business decisions. Identifies quality data sources, develops and validates predictive models, establishes data strategies and governance, deploys scalable production models, monitors performance, and communicates insights to cross-functional stakeholders. The role also supports continuous model improvement and mentors junior team members.

Lead commercial technology and data initiatives for EMEA commercial teams: manage cross-functional projects, drive adoption of SFA/TPM/CRM tools, ensure compliance (SOX, GDPR), perform business analysis, change management, stakeholder engagement, and SLA/vendor management.

Design, build, deploy, and improve ML- and LLM-powered services for intelligent automation and AI-driven product experiences. Develop reliable Python systems end to end, including monitoring, validation, observability, experimentation, and performance optimization. Partner with Engineering, Product, and Design teams to define metrics, evaluate models, run controlled experiments, analyze results, and ship scalable AI capabilities. Contribute to technical design and code reviews while improving prompting, retrieval, tool use, and orchestration strategies.

A 12-month graduate programme offering technology and AI/data science tracks. Associates may work in application development, DevOps, cybersecurity, data engineering, AI/ML, infrastructure, cloud, or advanced analytics. Responsibilities may include building GenAI and agentic AI solutions, developing ML models, applying MLOps, governing responsible AI, and collaborating with technical and business teams.

Lead DayOne’s EMEA Customer Implementation and Delivery function, overseeing customer onboarding from contract execution through service commencement. Responsibilities include implementation planning, programme governance, fit-out coordination, commissioning readiness, customer acceptance, executive engagement, risk mitigation, operational handover, and continuous improvement. The role also builds scalable processes, leads geographically distributed teams, manages customer escalations, and partners with Sales, Design, Construction, Commissioning, Operations, and Customer Success teams.

Leads end-to-end data delivery for complex consulting and custom research engagements across ASEAN and North Asia. Responsibilities include data sourcing, enrichment, modelling, validation, governance, quality control, client-ready delivery, stakeholder collaboration, and translating complex data into actionable insights. The role also drives AI, GenAI, automation, process improvement, coaching, and best-practice development.

Designs and maintains scalable batch and real-time data pipelines, data warehouses, lakes, marts, and APIs. Extracts, cleans, transforms, and integrates data using cloud platforms and big-data frameworks. Develops reliable ETL/ELT solutions, supports backend applications, applies data governance and security practices, and collaborates with architects, analysts, developers, designers, and project managers in an Agile environment.

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.

Join Micron as a Data Scientist to apply data analysis and machine learning expertise toward innovations in memory, storage, AI, and related products. The posting emphasizes company mission, inclusion, and application process; specific role responsibilities and qualifications are not listed.

Manage, maintain, and optimize critical database systems (SQL Server, Oracle). Perform installs, patches, backups, access control, monitoring, performance tuning, incident/change/problem management, on-call support, capacity planning, automation, reporting, and collaborate with global teams and site stakeholders.

Analyze semiconductor manufacturing data to identify yield detractors, build data pipelines, apply statistical and machine learning models for yield improvement, support DOE experiments, and create automated dashboards and reports for engineering stakeholders.

Lead Enterprise AI initiatives by designing, developing, and deploying AI/GenAI solutions. Partner with data engineers, technologists and business stakeholders to prototype, integrate, validate and benchmark LLM and advanced-model applications, manage expectations, and translate analytic results into business outcomes.

Lead end-to-end delivery of enterprise data and analytics solutions for retail banking, spanning requirements analysis, solution design, testing, implementation, governance, and production support for ML/NLP-enabled and rule-based decisioning systems.