Top Data Jobs in Singapore

Drive new business and expand existing accounts by defining sales strategies, developing pipeline (cold calling, email campaigns), managing end-to-end sales processes, coordinating vendors and inventory, maintaining sales reporting and forecasting, and sustaining vendor and partner relationships.

The Staff Data Scientist will optimize semiconductor manufacturing processes through data analysis, statistical modeling, and data visualization, collaborating closely with engineering teams.

Develop Green AI technologies focused on efficient machine learning, large language models, model optimization, parameter-efficient fine-tuning, retrieval-augmented generation, prompt engineering, and efficient inference. Conduct experiments, benchmark algorithms, analyze performance, contribute to research publications, and collaborate with multidisciplinary teams to translate research into deployable sustainable computing solutions.

Lead and execute Vantage's APAC public policy strategy, manage government and regulatory engagement, build and lead a regional policy team, coordinate with internal stakeholders, manage third-party advocates, ensure compliance with lobbying and anti-corruption laws, translate policy risks into business actions, and support sustainable, community-aligned growth across APAC markets.

The Senior Data Scientist will build and manage the intelligence layer of the Railway Common Data Platform, implement machine learning solutions, and enhance operational efficiency through data analytics and AI capabilities.

Drive enterprise sales for Semrush’s big data and emerging solutions. Serve as a subject-matter expert, partner with Account Executives on team selling, conduct product demonstrations, translate complex capabilities into customer value, identify expansion opportunities, provide product feedback, support launches and events, and maintain deep product knowledge. The role requires enterprise sales experience, solutions selling expertise, familiarity with DaaS, SaaS, or big data analysis, and strong storytelling skills.

Build, automate, and operate enterprise-scale data platforms using Databricks, Snowflake, Microsoft Fabric, Kubernetes, and cloud technologies. Responsibilities include Infrastructure as Code, CI/CD, GitOps, platform provisioning, reliability engineering, observability, security, governance, incident remediation, performance optimization, and FinOps. The role supports multi-environment deployments and self-service capabilities for data engineering and analytics teams.

Analyze global logistics, spend, invoice, and operational data to identify cost drivers, trends, anomalies, and optimization opportunities. Develop and maintain Tableau dashboards, automate reporting, support cost-to-serve models, and contribute to process mining and business intelligence initiatives using tools such as Celonis, Databricks, SAP, and Tableau. Collaborate with logistics teams worldwide, translate business requirements into analytics solutions, and present actionable findings to stakeholders.

Analyze and profile customer, KYC, onboarding, and reference data; design source-to-target mappings; define migration rules and validation criteria; identify data quality issues and anomalies; validate ETL pipelines; perform UAT, mock migration testing, reconciliation, and data verification; prepare technical documentation; and collaborate with business, compliance, governance, operations, and technology stakeholders to resolve migration issues.

Leads advanced analytics, reporting automation, marketing measurement, and AI-enabled analytics solutions. Builds dashboards, analytical datasets, statistical and machine learning models, data pipelines, validation frameworks, and API connectors. Partners with clients and cross-functional teams to translate business questions into measurable outcomes and actionable recommendations. Mentors analysts, reviews deliverables, supports project planning, and contributes to analytics capability development and new business initiatives.

Designs, develops, and optimizes large-scale data processing pipelines using Spark, Scala, Hadoop, Elasticsearch, and Quantexa. Responsibilities include data transformation, integration, performance tuning, data quality, governance, monitoring, documentation, and deployment on OpenShift. The role also supports system integration, coding, environment setup, CI/CD, troubleshooting, and technical solution development across project lifecycles.

Design, develop, automate, and maintain Power BI supply chain dashboards by extracting and transforming data from MRP/enterprise sources. Perform ETL, data quality checks, reporting, stakeholder engagement, project coordination, and provide insights to improve supply chain visibility and operations.

Supports corporate compliance across international data center operations by developing and maintaining policies, screening high-risk vendors and customers, conducting risk assessments, monitoring regulatory changes, delivering compliance training, and investigating breaches and whistleblower reports. The role also manages corrective actions, audit trails, compliance dashboards, and implementation of data privacy and governance requirements across multiple jurisdictions.

Lead cost management for MEP data centre construction projects from initiation to completion. Oversee cost planning, estimating, reporting, value engineering, risk and contract management, client/stakeholder engagement, team leadership, invoicing via Dynamics 365, and business development activities to meet budgetary and quality targets.

Manage client relationships as a subject matter expert, collaborating with Account Executives to drive revenue, engage clients, and provide product insights for innovative solutions.

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.

Leads advanced analytics, measurement, reporting automation, and AI-enabled analytics solutions for clients and internal stakeholders. Develops marketing mix models, attribution, predictive models, segmentation, dashboards, data pipelines, and analytics-ready datasets using SQL, Python, cloud platforms, and BI tools. Presents insights to stakeholders, supports client consulting and business development, mentors analysts, and advances data quality, governance, measurement methodologies, and analytical capabilities.

Lead Customer 360 data engineering initiatives across Customer and Sales domains. Design data integration, ingestion, curation, governance, quality, harmonization, and common data models. Build scalable cloud-based data capabilities and integration pipelines while supporting data products, use cases, and analytics. Collaborate with business owners, regional partners, and technology teams to define strategy, roadmaps, prototypes, and MVPs, serving as a subject matter expert in Customer 360 data.

Design, build, deploy, and improve OCR, computer vision, and LLM-based systems for intelligent document understanding. Develop production ML services in Python, monitor quality and performance, run controlled experiments, optimize model behavior, and collaborate with product and engineering teams to deliver AI capabilities.

Lead design and delivery of AI-powered automation, Copilot agents, advanced analytics, and monitoring solutions for global Healthcare Compliance. Translate business problems into scalable data-driven solutions, partner with governance and technology teams, and mentor stakeholders while implementing APIs, BI dashboards, process mining, and Cloud-based generative AI capabilities.

Lead single-threaded product and technical ownership for Client Intelligence & Data, defining APIs and event-driven architectures to deliver merchant-facing analytics, KPIs, and reports. Drive platform strategy toward AI-driven insights, enforce production reliability and automated QA, champion You Build It You Run It culture, partner cross-functionally to scale multi-tenant analytics capabilities, and prioritize work using evidence-based frameworks.

Perform high-level video captioning, action-based timeline segmentation, and visually-verifiable action labeling. Review and correct AI-generated captions, meet accuracy benchmarks, follow strict guidelines, and complete certification.

Leads the bank’s AI and data assurance strategy, overseeing model validation, AI risk mitigation, data quality, privacy, governance, controls, monitoring, regulatory reporting, stakeholder training, and team leadership. Ensures AI and data initiatives are ethical, compliant, secure, reliable, and aligned with financial-services regulations and internal policies.

Lead development and execution of company-wide data, analytics, and AI strategy. Build and manage multidisciplinary teams, govern data quality and compliance, oversee architecture and production ML/AI deployments, select and maintain data platforms and tooling, partner with business stakeholders to deliver high-impact use cases, and measure ROI while driving innovation and adoption.

Design, deploy, and maintain AWS and Databricks data infrastructure, data lakes, and scalable ETL pipelines. Build custom ingestion services and connectors using Airbyte, Go, and Python; optimize performance, reliability, monitoring, and data quality. Implement cloud data governance, security, access controls, encryption, and compliance practices while collaborating with platform engineers, analysts, and stakeholders.