Top Data Jobs in Singapore

Design, build, secure, and operate highly available data centre networks, including leaf-spine fabrics, routing, switching, firewalls, load balancers, segmentation, and inter-data-centre connectivity. Troubleshoot mission-critical network issues, improve reliability, and manage capacity and performance. Develop Network-as-Code automation for provisioning, validation, testing, compliance, and drift detection. Apply telemetry, AI, and AIOps techniques while collaborating with cloud, compute, storage, cybersecurity, and application teams.

Design and operate enterprise AI platforms for a banking group, including multi-agent frameworks, LLM inference infrastructure, MLOps pipelines, and hybrid AWS/on-premises deployments. Build production AI services, optimize GPU utilization and inference latency, manage model lifecycles, establish CI/CD and observability, and provide daily platform operations. The role requires strong Python, cloud, AI framework, inference-stack, Kubernetes, infrastructure-as-code, and DevOps expertise, with AVP and VP experience levels ranging from 4+ to 8+ years.

Design, build, and operate scalable logging and operational data platforms across on-premise, government cloud, AWS, Azure, and hybrid environments. Responsibilities include log ingestion, routing, enrichment, storage, indexing, search, streaming, data integration, Infrastructure as Code, CI/CD, security, governance, reliability engineering, monitoring, incident response, and operational support. The role also defines schemas, data contracts, retention policies, platform interfaces, and reusable capabilities for downstream engineering, analytics, dashboards, and automation consumers.

Designs and operates observability across on-premises, cloud, hybrid infrastructure, applications, and networks. The role establishes OpenTelemetry instrumentation standards, telemetry collection, dashboards, SLIs, SLOs, alerting, and operational health indicators. Responsibilities include integrating telemetry sources, supporting incident investigation, improving service reliability, managing retention and security requirements, automating deployments with Infrastructure as Code, and maintaining runbooks. The engineer collaborates with application, infrastructure, network, security, platform, and operations teams and participates in on-call support.

Build and operate production-grade data pipelines across on-premises and cloud environments. Responsibilities include data ingestion, ETL/ELT, transformation, modelling, quality validation, lineage, monitoring, secure integration, and reusable analytical data products. The role supports dashboards, reporting, machine learning, and operational analytics while implementing CI/CD, Infrastructure as Code, data governance, reliability controls, incident response, and production support.

Own pricing and retail analytics initiatives, including decision systems, reports, metrics, statistical analysis, and business insights. Lead end-to-end projects, translate complex data for stakeholders, influence product and strategy decisions, and collaborate with Pricing, Retail Commerce, 3P Commerce, Promotions, developers, and analysts. Ensure data quality, improve reporting systems, solve ambiguous problems, and provide strategic guidance in a fast-paced e-commerce environment.

Annotate and segment videos, write objective captions, label visually verifiable actions, and review AI-generated captions for accuracy and consistency. Specialists must follow detailed guidelines, maintain at least 95% benchmark accuracy, and complete a paid certification process involving training, platform practice, and five certification tasks before accessing ongoing production work.

Lead Data Scientist responsible for developing and deploying multilingual large language models, building datasets, and improving AI safety alignment.

As a Data Scientist, you will translate business problems into data analytics solutions, manage the ML lifecycle, and improve driver incentives through statistical analysis.

Lead DayOne's group tax function across APAC and Europe, owning compliance, transfer pricing, planning, and structuring. Advise senior leadership on tax legislation, support new market entry structuring, manage external advisors, review tax provisioning, and develop tax strategies aligned to the company's expansion roadmap.

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.

A 12-month graduate programme offering rotations and hands-on projects in Technology or AI & Data Science. Responsibilities include building and deploying software, cloud and infrastructure work, cybersecurity practices, and developing ML/GenAI solutions (LLMs, agents, MLOps). Participants receive structured training, mentoring, and exposure to senior leaders while working on real enterprise problems to deliver scalable, secure, and impactful solutions.

Develop and maintain end-to-end Xceptor data automation and integration solutions for banking and capital markets. Configure MessageHub channels, Mail integrations, REST/SOAP APIs, workflows, parsing, routing, validation, transformation, reconciliation, and exception handling. Integrate upstream transaction systems with downstream accounting, reporting, and analytical platforms. Monitor production workflows, troubleshoot failures, optimize performance, and collaborate with architects, analysts, and financial-market SMEs.

Supports investor relations, capital-raising strategies, equity and debt financing, market and peer analysis, board reporting, and communications with investors, analysts, banks, advisors, and executives. The role prepares earnings materials and presentations, evaluates financing opportunities, monitors covenants and credit ratings, and helps optimize the company’s capital structure and access to capital.

Develop and maintain advanced inventory and supply planning models, inventory optimization targets, scenario analyses, dashboards, and KPIs. Use Python, SQL, BI tools, predictive modeling, and machine learning to support supply planning, S&OE/S&OP, demand-supply coverage, capacity constraints, and inventory health. Partner with planning teams to improve data quality, automation, governance, model reliability, and executive decision-making.

Own commercial strategy and operations for enterprise pharma and AI accounts: drive pilots-to-revenue, account expansion, pipeline management, pricing, forecasting, and deal strategy. Build cross-functional relationships, push deals through legal/procurement/IT, act as CEO counterpart to shape strategy and product roadmap, and be highly present in person with customers and at conferences.

Analyze large-scale transactional, operational, and customer datasets; build visualizations, machine learning models, and experiments; translate complex findings into clear recommendations for operational teams and executives; and apply analytical software, databases, visualization tools, and programming languages in a fast-paced blockchain environment.

Design, build, and scale data infrastructure for LLM training, fine-tuning, evaluation, and RAG. Implement and maintain data architectures, pipelines (batch and streaming), org-level IAM and governance, cost/performance optimizations, analytics/dashboarding, AI-assisted ops and internal automation tools, and support multi-cloud production workloads.

Perform high-risk document and account servicing tasks, act as SME, manage exceptions and escalations, support audits and regulatory requests, reconcile operational reports, liaise with vendors, ensure SOP compliance, and drive process improvements while providing backup team lead coverage.

Manage daily Data team operations, research and analyze datasets, build internal and external reports (including an annual Startup Ecosystem Ranking), and maintain/improve Python scripts and data infrastructure to deliver actionable insights.

Design, develop, and deploy production-ready AI applications and scalable DataOps/MLOps pipelines for avionics manufacturing. Build LLM/RAG/agent-based solutions, integrate enterprise and manufacturing systems, implement CI/CD and containerized deployments, ensure security/compliance, and collaborate with stakeholders to deliver measurable operational improvements.

NTT DATA's Associate Graduate programme provides structured learning, mentorship, and hands-on exposure across cloud, data, AI/ML, application development, automation, infrastructure and cybersecurity. Graduates work on real client projects, earn certifications, build technical and professional skills, and explore specialised career pathways such as Cloud Engineering, Data Engineering, AI/ML, and Cybersecurity.

Manage and grow strategic regional ASEAN accounts as a quota-carrying client manager. Drive ACV, revenue, renewals and expansions; build executive relationships; identify cross-sell/upsell opportunities; coordinate country teams, solution specialists and delivery stakeholders; manage full sales lifecycle, forecasting, pipeline, and regional account governance.

Develop, train, fine-tune, evaluate, and deploy AI/ML models and LLM-powered data products. Build end-to-end model pipelines, feature engineering, monitoring, and production deployment. Apply generative AI for summarization, classification, knowledge extraction and semantic search. Collaborate with product, engineering, and business teams and integrate third-party tools and open-source models.

Leads regional Payment Operations transformation, service excellence, and AI-enabled digital initiatives. Drives predictive analytics, automation, workflow digitization, and scalable technology solutions using Python, SQL, Power BI, Power Automate, APIs, and Generative AI. Oversees projects from business case through implementation, benefits realization, governance, operational readiness, and regional rollout. Partners across Operations, Technology, Product, Risk, Compliance, vendors, payment networks, and country teams to improve productivity, resilience, controls, quality, and client outcomes.