Top Data Jobs in Singapore

Lead global analytics and data science teams supporting semiconductor manufacturing. Drive yield and process optimization through SQL, sensor, and fabrication-tool data; apply statistical modeling and machine learning to reduce defects; support DOE experiments; build automated dashboards; and manage cross-functional delivery portfolios. Mentor technical talent, improve data quality and platform performance, standardize modern data stacks, and partner with engineering and business leaders on prioritization, risks, and dependencies.

Supports the delivery of data centre and mission-critical construction projects across planning, design, procurement, construction, commissioning, and handover. Responsibilities include schedule and milestone monitoring, risk and change control, reporting, stakeholder coordination, technical submission reviews, budgeting, documentation management, site inspections, and operational readiness. The role works with clients, consultants, contractors, vendors, and internal teams while promoting health, safety, quality, and project governance.

Build and maintain batch and streaming data pipelines, data models, ingestion workflows, Airflow orchestration, cloud infrastructure, CI/CD, and backend data services. Support CDC, messaging, real-time processing, vector database pipelines, embeddings, semantic search, and RAG knowledge bases. Collaborate with senior engineers, AI teams, and business stakeholders to deliver reliable datasets and services for banking use cases including risk, fraud, customer engagement, and automation.

Lead end-to-end delivery of complex client projects involving data warehouse migration and AI. Responsibilities include project planning, requirements gathering, stakeholder management, Agile or Waterfall delivery, testing, data analysis, governance, risk management, executive reporting, client relationship support, and coaching delivery teams. The role bridges business and technical stakeholders while ensuring projects meet scope, timeline, budget, quality, and business-value objectives.

Leads programme-wide scientific data governance, QA/QC, auditing, documentation, database development, data tracking, and version control. Establishes protocols for research data, models, and assumptions; collaborates with multidisciplinary research teams; conducts internal audits; resolves data discrepancies; and prepares reproducible data subsets for publications, reporting, funding submissions, and regulatory review.

Supports paleoseismology, neotectonics, and geodetic research through geological fieldwork, trench investigations, sample processing, levelling-data digitization, quality control, and analysis. Responsibilities include geological and geodetic data management, integration of levelling, InSAR, and GNSS observations, technical reporting, and collaboration across multidisciplinary research teams. The role may involve demanding fieldwork, regional travel, and mentoring undergraduate interns.

Supports pharmaceutical laboratory quality operations by developing Power BI and digital tools, analyzing equipment and inventory data, managing laboratory supplies and retain samples, coordinating calibration and maintenance, and ensuring cGMP, safety, 5S, and contractor-management compliance. The intern will collaborate with laboratory stakeholders, perform process improvements, and present data-driven recommendations to quality leadership.

Build full-stack tools, backend services, APIs, dashboards, and data workflows for assessing and improving AI training data and evaluations. Partner with quality and research teams to inspect agent trajectories, validate graders, measure quality, investigate workflow issues, and turn internal prototypes into reliable production platform capabilities.

Manage the design, creation, validation, maintenance, and lifecycle of master data in SAP S/4HANA for manufacturing plants and distribution centers. Responsibilities include material masters, BOMs, recipes, workflows, data quality scorecards, analytics, reporting, governance standards, business continuity data, audits, and problem-solving workshops. The role partners with global data services and business process teams to support operational excellence and compliance.

Oversee portfolios of Generative AI data operations projects, managing delivery, capacity planning, vendors, budgets, quality, risks, automation, and client reporting. Coach project managers and coordinators, collaborate with recruiting and finance, enforce data security and compliance, and improve processes across distributed teams.

Support fund management and finance teams through financial modeling, investor reporting, valuation and NAV processes, portfolio performance tracking, budgeting, cash-flow management, and ad hoc analysis. Monitor data center asset metrics, maintain dashboards, coordinate with internal stakeholders, and prepare materials for investors, boards, investment committees, and asset reviews.

Leads data migration and analysis projects for KYC and CLM platforms. Gathers requirements, documents business rules and data mappings, analyzes data quality and lineage, defines cleansing and transformation rules, and validates migration results through SIT and reconciliation. Coordinates business, technical, QA, and project stakeholders; tracks defects, risks, remediation, and traceability. Supports project planning, client presentations, team leadership, and business development.

Lead technical strategy with channel partners across ASEAN to build repeatable Microsoft Cloud and AI Workforce offerings (Copilot, Power Platform, Agents). Drive architecture design, workshops, POCs, offer development, partner enablement, and co-sell execution to convert technical capability into scalable revenue and customer outcomes.

Lead finance data governance for Accounts and related master data, including standards, policies, documentation, workflows, data quality controls, mappings, hierarchies, and golden records. Manage governance intake, stakeholder forums, workflow tool enhancements, testing, defect resolution, training, and process improvements. Support finance data projects and user queries while maintaining alignment with Kenvue’s Common Information Model.

Develops Microsoft 365 and Power Platform solutions, dashboards, reports, workflows, integrations, and data visualizations for legal investigations and litigation. Supports internal investigations through open-source research, forensic data review, information analysis, and government inquiry support. Partners with Legal, Compliance, Audit, Information Security, and Technology teams while ensuring privacy, cybersecurity, governance, and stakeholder requirements are met.

Supports product managers with app roadmaps and UAT testing while analyzing user behavior and product performance. Collects and cleans data, builds dashboards and visualizations, conducts A/B testing, and delivers reports and actionable recommendations. Collaborates with customer support, user research, and UX teams to identify pain points and optimize app features and user experiences.

Design and deliver production-ready AI and data science solutions across CRM, retail, marketing and operations. Build ML models, GenAI/RAG pipelines, feature engineering and training workflows; collaborate with data engineering to deploy, monitor and optimize models; run experiments and measure business impact while ensuring responsible AI, security and governance.

Design and implement advanced smart manufacturing solutions in scheduling, mathematical optimization, and discrete event simulation. Build data analytics and applications to provide actionable insights, collaborate globally to deploy solutions across manufacturing sites, and integrate AI/OR hybrid methods to improve production performance and benchmarking.

Lead data science strategy for AML and financial crime risk controls. Develop AI-powered screening, entity resolution, graph and network intelligence, anomaly detection, transaction monitoring, and proactive discovery of emerging threats. Partner with Product, Engineering, Compliance, and Operations to deliver scalable production controls, influence the roadmap, establish reusable frameworks, and mentor data scientists.

Leads enterprise customer engagements delivering AI, machine learning, generative AI, NLP, RAG, and agentic AI solutions. Designs and deploys production systems across cloud platforms, establishes LLMOps practices, integrates solutions with client workflows, presents technical strategies, manages stakeholders, and mentors regional team members. Requires deep expertise in modern ML frameworks, large language models, data platforms, governance, and customer-facing technical delivery.

Leads DayOne’s global brand strategy, identity, creative direction, events, sponsorships, digital brand governance, and thought-leadership presence. The role ensures consistent brand execution across international markets, manages agencies and creative partners, oversees major brand assets and experiences, and tracks brand performance through defined KPIs. It requires strong cross-functional leadership and the ability to translate business strategy into differentiated brand expression for the digital infrastructure ecosystem.

Deliver data science consulting projects for marketing, customer, and product use cases in luxury, consumer goods, and retail. Responsibilities include data analysis, KPI design, experimentation, machine learning, generative AI, data engineering, visualization, stakeholder storytelling, and solution deployment. The role also supports transformation, training, thought leadership, R&D, and business development.

Lead data migration analysis projects involving data profiling, remediation, quality validation, test case execution, SIT and UAT support, and Power BI reporting. Coordinate project teams, validate data mappings and transformations, manage defects, document findings, and provide recommendations for KYC and CLM compliance. The role also includes project planning, stakeholder presentations, and support for business development initiatives.

Performs document retrieval, customer communication preparation, data entry, control checks, exception follow-up, record validation, reporting, and document routing. Maintains accurate filing, audit readiness, and compliance with procedures and service-level agreements. Coordinates with internal teams, law enforcement, legal firms, and vendors, while supporting user acceptance testing, template updates, and operational initiatives. Requires strong attention to detail, organization, communication, and the ability to manage high-volume routine tasks accurately.

Develop robotics datasets and evaluations for embodied AI systems. Responsibilities include defining data schemas, annotations, quality standards, collection protocols, validation tools, and review workflows. The role also involves running experiments to assess how data quality and structure affect model performance, collaborating with research, engineering, vendors, and customers, and taking research tools from conception through deployment.