Top Data Jobs in Singapore

Provides technical and methodological support for digital humanities, arts, and social sciences research. Responsibilities include coding, dataset collection and preparation, web and mobile application development, cloud service support, website maintenance, digital methods training, research proposal assistance, software development standards, and service improvement. The role also supports academic events and collaborates with researchers and technical teams across NTU and Singapore.

Applies data science, operations research, predictive analytics, forecasting, simulation, and optimization models to air network planning and operational decisions. Operates and supports AI, machine learning, and generative AI solutions in GCP using services such as BigQuery, Vertex AI, and Gemini. Analyzes complex datasets with SQL and Python, develops dashboards and reporting tools, evaluates scenarios, supports process improvement, and communicates recommendations to technical and business stakeholders.

Develop and maintain ETL data pipelines, optimize data flow and delivery, automate manual processes, and design scalable data infrastructure. Gather telemetry data to improve system efficiency and business metrics. Collaborate with cross-functional teams on requirements and data products, using databases, workflow tools, microservices, and APIs. Preferred experience includes Agile development, monitoring, fault-tolerant pipelines, big data technologies, and search engines.

Supports banking compliance and data transformation initiatives across AML, KYC, financial crime, regulatory reporting, and data governance. Gathers requirements, facilitates stakeholder workshops, performs data analysis and mapping, documents user stories and functional specifications, assesses data quality, and supports UAT, project governance, and successful delivery across business and technology teams.

Designs and evolves enterprise data architecture supporting global manufacturing, supply chain, procurement, logistics, quality, and engineering operations. Defines data models, integration patterns, governance standards, metadata, lineage, and reusable data products across enterprise systems and cloud platforms. Partners with engineers, architects, AI specialists, governance teams, and business leaders to enable analytics, AI, digital twins, reporting, and smart manufacturing initiatives.

Develop machine learning, statistical, optimization, computer vision, Generative AI, and Agentic AI solutions for smart manufacturing. Analyze operational data, build production-ready AI applications, support cloud deployment and model monitoring, and collaborate with manufacturing, engineering, supply chain, quality, IT, and software teams to improve quality, productivity, reliability, and decision-making.

Develops, enhances, tests, installs, and documents software applications for internal and external clients. Responsibilities include coding, database maintenance, performance optimization, troubleshooting, platform adaptation, client consultation, requirements analysis, and technical advising. The role requires advanced programming expertise, software development process knowledge, Agile/Scrum experience, cross-functional collaboration, and proficiency with Java, additional programming languages, operating systems, and SQL.

Own the end-to-end lifecycle of data-driven derivatives product initiatives, from identifying opportunities through launch and optimization. Analyze trading and user behavior data, define product roadmaps and success metrics, design experiences that improve engagement and conversion, and collaborate with Engineering, UX, Marketing, Compliance, and global stakeholders. The role requires derivatives trading knowledge, strong analytical and product management skills, bilingual English/Mandarin communication, and experience shipping data-driven products.

Supports enterprise data governance initiatives across data lineage, data quality, data catalogues, taxonomy, discovery, and impact analysis. Assists with data analysis, reporting, dashboard development, stakeholder requirements, process improvements, and ad hoc risk-management projects. The internship provides exposure to BCBS239 principles, regulatory reporting, data governance frameworks, and tools for managing enterprise data assets.

Designs and delivers data architecture solutions, creates secure production code, evaluates technologies, guides architecture governance, and applies AI-assisted practices to improve data frameworks, resiliency, and security.

Design and deploy real-time ML models and credit risk frameworks to detect fraud and assess merchant lending risk. Translate business needs into scalable analytics, monitoring, and decision-support tools. Partner with product, engineering, and operations to productionize models and improve risk visibility and decision quality.

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.

Lead data acquisition and partnership activities for Transport AI, developing a prioritized multimodal data roadmap, negotiating data access with agencies and industry, enforcing data standards and governance, building secure ingestion platforms, and working with legal, cyber and AI teams to onboard datasets for analytics and AI use cases.

The role involves ensuring end-to-end performance and power readiness of Data Center SSD programs through technical execution, analysis, and leadership across teams.

Manage and optimize high-load Microsoft SQL Server databases, including advanced T-SQL development, query and execution-plan optimization, indexing, locking, memory, disk performance, AlwaysOn availability, maintenance, recovery, security, integrity checks, monitoring, and incident resolution. Support analysts and ML engineers with reliable data access across databases reaching tens of terabytes.

Build and maintain scalable enterprise data platforms, pipelines, integrations, and reusable data products for global manufacturing operations. Implement data governance, quality monitoring, metadata, lineage, and master data practices. Develop cloud-native, batch, streaming, and event-driven solutions supporting analytics, AI, reporting, smart factories, and digital twins. Collaborate with architects, engineers, data scientists, and operations stakeholders while applying DevOps, observability, and CI/CD practices.

Analyze e-commerce data across Reolink’s official website and Amazon platforms to generate insights, improve profitability and performance, and support product decisions. Build data pipelines, dashboards, APIs, and e-commerce metrics systems; validate data quality, investigate issues, and collaborate with product management, engineering, design, and data engineering teams to drive data-informed growth.

Coordinates local and overseas Community Immersion Programme projects from planning through follow-up. Manages timelines, stakeholders, logistics, mentor and partner matching, participation tracking, reporting, dashboards, and feedback analysis. Uses data, digital tools, automation, and AI applications to improve programme processes and efficiency while supporting programme growth and stakeholder engagement.

Analyzes international trade, tariff, customs, shipment, and trade agreement data; prepares reports and recommendations on risks, costs, duty optimization, and trade strategy. Monitors import/export compliance across China, Europe, and Asia, maintains SAP/MIC trade data, resolves discrepancies, supports customs reconciliation, researches regulatory changes, and identifies automation and process improvement opportunities. Collaborates with logistics, supply chain, finance, legal, compliance, and regional trade teams.

Maintain bond and issuer reference data across treasury systems, ensuring accurate attributes, timely request processing, and adherence to SLAs and controls. Investigate data issues, collaborate with dealers, finance, custodians, and processing teams, and support UAT, process documentation, STP improvements, and data transformation initiatives. The role requires financial markets knowledge, bond settlement experience, strong analytical skills, and proficiency with Murex, Bloomberg, custodian systems, and Microsoft 365.

Lead and coordinate card-network financial integrity programs (fraud, disputes, chargebacks). Maintain governance, trackers, remediation, controls, and documentation. Translate network requirements into internal policies and playbooks, coordinate cross-functional remediation, prepare leadership/audit materials, identify process gaps, and standardize global program execution across Compliance, Risk, Legal, Product, and Operations.

Build and operate production-grade AI data pipelines and financial knowledge services for equities content. Responsibilities include processing text, tables, documents, and multimedia; creating knowledge bases and search indexes; engineering RAG retrieval and citation systems; integrating LLMs and NLP models; managing orchestration, APIs, quality, cost, observability, reliability, and scalable production operations.

Lead the go-to-market and sales strategy for LMAX’s market data business across APAC. Identify, qualify, negotiate, and close opportunities with brokers, banks, hedge funds, and other financial-market clients. Develop pricing, licensing, and distribution models; serve as a market-data subject matter expert; and collaborate with account management, technology, product, and commercial teams to drive revenue, market share, product improvements, and successful client partnerships.

Analyze and reconcile financial data, investigate discrepancies, trace data origins, and automate manual validation checks using SQL and Python. Build and maintain Finance dashboards, document datasets, and make missing or inconsistent data visible. The role involves production data, reporting pipelines, version control, review processes, and clear communication of findings. No professional experience is required, but candidates should be numerate, detail-oriented, comfortable questioning data, and able to explain technical discrepancies clearly.

Build and operate ingestion and ELT pipelines, maintain metadata repositories and internal data tools, implement data-quality checks, reconcile financial data, investigate anomalies, and support analysts. The role includes backend service development, production ownership, AWS-based platform work, and integrating LLM/RAG capabilities into data tools.