Top Data Jobs in Singapore

Lead the development of AI and ML solutions for underwriting, manage a team of data scientists, and ensure compliance and governance in initiatives.

Seeking a Data Analyst to analyze data sets, generate reports, and support data-driven decision-making within the company.

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.

The Staff Software Engineer will design high-performance backend services, manage distributed state, ensure system resilience, and implement cloud-native architectures with advanced engineering principles.

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.

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.

Early-career intern will support AI projects for compliance and risk (KYC, KYB, EDD). Tasks include testing and optimizing LLM/Agent workflows, reviewing prompts and model outputs, documenting findings and edge cases, supporting small-scale implementations, and performing operational analysis to improve processes.

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.

Work with cross-functional teams to design, evaluate and deploy NLP and generative-AI systems. Build evaluation frameworks, run experiments, perform error analysis, and help productionize and monitor model improvements while ensuring reproducibility, responsible AI and clear communication to stakeholders.

Join a team building AI-enabled products for government communications. Define ML/NLP problems, build evaluation frameworks and datasets, run experiments, perform error analysis, recommend and integrate model improvements, ensure reproducibility and responsible AI compliance, and communicate findings to technical and non-technical stakeholders.

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.

Collect, analyze and interpret complex data to produce insights, forecasts, and reports. Build and maintain Salesforce dashboards and BI visualizations, conduct data quality checks, develop data governance, and support stakeholders through training and workshops. Use statistical modelling and AI tools to automate reporting and improve decision-making.

Support data management and governance by managing data assets, ensuring data quality, standards, and policies; publish and protect data for analytics; contribute to analytic platforms and reporting solutions; work on moderately complex projects with general guidance.

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.

Lead partner-focused analytics for APAC: investigate conversion, churn, and payment-funnel issues; analyse large operational datasets; build dashboards and automated reports; perform root-cause analysis; collaborate with commercial teams and external partners; apply analytics engineering and emerging AI tools to improve partner outcomes.

Lead and build BNY's Singapore Applied AI team to identify, design, and deliver production-grade AI/ML and LLM solutions. Drive end-to-end delivery from problem framing, prototyping, evaluation, deployment, monitoring, and adoption while embedding responsible AI, governance, and cross-functional stakeholder alignment.

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.

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.

Lead end-to-end delivery of enterprise data and analytics solutions for retail banking, spanning requirements analysis, solution design, testing, implementation, governance, and production support for ML/NLP-enabled and rule-based decisioning systems.

The Software Engineer for Data Infrastructure & Acquisition at Speechify will enhance data collection, manage infrastructures, and work with AI scientists to develop large-scale datasets.

Translate business problems into data solutions: collect/explore data, build and evaluate statistical and AI models, deploy models as code (microservices), develop AI agents and RAG solutions using vector/graph databases, apply 3D/CAD and mesh algorithms, and support data governance, migration, and policy to maintain model lifecycle and business value.

This role involves designing and maintaining data pipelines, managing APIs, collaborating with teams, and ensuring data quality and governance.

Lead HUD's data quality strategy for RL training data: build QC systems, validate synthetic data at scale, design evaluation experiments, partner with researchers and vendors, convert research insights into production validation pipelines and tools, and mentor research engineers.

The Data Scientist will develop AI-driven solutions for supply chain optimization, utilizing advanced analytics, machine learning, and statistical modeling to deliver business impact.