Top Data Jobs in Singapore

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.

Leads commercial activities for global data center customer prospects, including strategic pricing, bid and RFP support, contract risk assessment, deal approvals, costing, renewals, churn analysis, sales forecasting, and pipeline analysis. Partners with Sales, Product, Legal, and other business units to improve profitability, digitize quotation processes, and implement commercial initiatives. Requires strong knowledge of ICT and data center markets.

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 enterprise data product and Data-as-a-Service strategy, delivery, operationalization, governance, and adoption within a regulated banking environment. Build reusable, governed data products supporting analytics, AI, reporting, and business decision-making. Establish operating models, metadata and lineage standards, quality controls, self-service consumption channels, and Centre of Excellence practices. Partner with senior stakeholders, engineering, technology, governance, risk, and business teams to prioritize use cases, manage delivery, enable AI context, and track measurable value.

Design, build, and maintain data models, ETL pipelines, dashboards, and APIs to support industry models, research, and consulting. Ensure data accuracy, completeness, and observability while integrating new datasets and cloud infrastructure. Collaborate with analysts and stakeholders to deliver robust, modular production data systems with minimal supervision.

Design, build, and maintain the Consumer Banking Singapore DataMart; extract, clean and analyze data; create dashboards and automated reports; support stakeholders with insights, decision support, and data-driven business cases; document data catalog and improve data processes.

Triage and resolve Master Data Management (Party, Risk, Reference) issues in Stibo STEP, run targeted data-cleansing sprints, monitor data quality dashboards, support releases/UAT, and maintain documentation and playbooks to prevent recurring data issues.

Lead data discovery, governance, and master data management for supply chain. Define processes, KPIs, and quality metrics; translate business needs into data requirements; resolve data issues; run workshops and collaborate across technical and business teams to improve data quality and implement solutions.

Build and maintain dashboards tracking activation, retention, task success, and agent reliability; analyze agent run data to locate failures and stalls; design instrumentation and metrics; support experiment design and readouts; produce reproducible analyses and actionable recommendations for product and engineering.

Manage pre- and post-contract cost services for complex construction and mission-critical data centre projects. Prepare estimates, cost plans, tendering, procurement, change control, forecasts, and client reports. Provide commercial input to value engineering, cost optimisation for MEP-heavy packages, and support governance, risk management, and knowledge sharing.

Lead cost management for large-scale data centre MEP packages, driving cost control, commercial strategy, estimating, procurement support, contract management (NEC/FIDIC), reporting, and team leadership across design, construction and commissioning phases.

Support cost management for data centre projects including cost estimates, quantity take‑offs, tender support, contract administration, cost tracking, reporting, and stakeholder coordination under senior guidance.