Top Data Jobs in Singapore

Assist in building and maintaining data ingestion pipelines and storage for AI workflows. Implement deployment, security, and monitoring for applications; collaborate with stakeholders and design teams; test and validate data verification and AI workflows; document solutions and follow best practices while continuously learning new tools.

Lead and mentor a logistics analytics team to deliver insights on fleet performance, delivery efficiency, and cost optimization. Shape analytics roadmap, design performance metrics and AI data products, apply decision science and operations research, manage end-to-end analytics execution, and present executive-ready recommendations to drive measurable improvements.

Build and productionize ML systems for personalization, search, and recommendations. Apply statistical and ML models using Python and SQL, collaborate with stakeholders, and measure business impact across cloud environments.

Operate, maintain, and optimize hybrid cloud Data and AI platforms (Cloudera CDP/CML, Hadoop, Spark) across AWS and on-prem. Perform platform upgrades, security patching, container/Kubernetes/OpenShift administration, monitoring, troubleshooting, and automation using Shell/Python. Collaborate with Infrastructure, Security, SRE, and Data/ML teams to ensure availability and scalability of AI/ML and Generative AI services (SageMaker, EMR, Bedrock).

Analyze casino operations and product performance, build models and ML solutions for floor optimization, demand forecasting and manpower scheduling, create dashboards and A/B tests, collaborate with Operations, Marketing, BI, and IT to translate analytics into business strategy and operational improvements.

Lead development and evolution of the Group's AI risk framework, translate policy into practical controls, engage business and tech teams, monitor AI use cases, guide resolution of control gaps, and align frameworks with regulatory expectations and industry developments.

The Associate Director will lead engineering strategy, oversee multiple teams, ensure quality delivery of applications, and promote a high-performing, innovative engineering culture.

Design, build, test and support batch and streaming data pipelines and curated datasets on a modern Lakehouse and AI data platform. Implement data modelling, schema evolution, partitioning and data quality controls. Partner with platform teams and consumers, contribute tooling and standards, and lead delivery for workstreams while supporting junior engineers.

Lead advanced analytics and ML projects: perform EDA, feature engineering, statistical modeling, and build/optimize production ML and Generative AI solutions (LLMs, embeddings, RAG). Collaborate with engineering and MLOps to deploy and monitor models, create visualizations and dashboards, translate insights for stakeholders, and mentor junior team members.

Lead a cross-functional AI/ML team to define strategy, design and deploy scalable production AI solutions (Generative AI, NLP, vision, time-series), drive research, ensure code quality and CI/CD, mentor engineers, and collaborate with business partners to deliver impactful decision-science products.

Develop and implement computer vision algorithms, evaluate model performance, and integrate solutions into larger systems, while maintaining documentation and staying updated on technology advances.

The Senior Data Scientist will develop AI solutions for gamers, focusing on Reinforcement Learning and Generative AI, collaborating closely with game developers and engineers.

The Senior Data Engineer will lead AI Data Engineering initiatives, architect and manage data infrastructure, and optimize data pipelines for AI and ML applications using various tools and technologies.

Analyze payment flows and network fees, translate network specifications into billing models, identify cost-saving opportunities, partner with engineering, product, and finance, maintain fee accuracy and alerts, document and scale operational processes, and educate stakeholders.

Conduct research and development on LLM technologies (RAG, prompt engineering, knowledge-grounded dialogue). Improve foundation model performance via data acquisition, evaluation, SFT, reward modeling, and RL. Prototype downstream AI/agent products for Binance and track academic and industry advances.

Develop, deploy, and maintain LLM pipelines and RAG QA/search systems; design and optimize prompts and multi-agent LLM architectures; operate multi‑GPU/cluster inference; build evaluation pipelines for model quality, bias, and hallucination; collaborate with product and CS teams to integrate conversational AI.

Design, build, and manage large-scale search and content recommendation systems using machine learning and personalization techniques. Collaborate with content, product, and business teams to define success metrics, drive AI product improvements, and maximize content value and user impact.

Six-month junior fixed-term role to design and develop LLM-based agents for Web3 scenarios, build token research and summarization agents, assist in trading agent development using market and on-chain data, and experiment with prompt engineering, memory, and multi-agent orchestration and evaluation.

Support distribution & logistics team with data collection, analysis, and audits. Create templates, work with external partners, benchmark performance, audit freight documentation, assist monthly customs compliance reporting, generate management reports, and support SOP and project implementation.

The Consultant/Senior Consultant will manage projects, develop practice-related content, and enhance data delivery methodologies, ensuring timely and quality project completion.

The role involves leading data governance and finance transformation projects, supporting client initiatives, and implementing enterprise data strategies for financial institutions.

Lead design and execution of data and AI governance for a regional digital bank: define policies, lifecycle frameworks for ML/GenAI, implement governance tools and dashboards, coordinate incident response, and partner with data, MLOps, product, tech and risk teams to embed privacy, fairness and regulatory compliance across AI and data systems.

Manage and maintain SharePoint farms and site collections, administer SQL Server for SharePoint and applications, implement HA/DR, automate tasks with PowerShell, ensure security/compliance, support hybrid M365 integrations, monitor systems, perform incident resolution and on-call duties, and participate in disaster recovery testing.

Own and standardize QA/QC processes and templates, run program-level audits across construction projects, support pre-construction quality input, consolidate and analyze project quality data, identify systemic trends and root causes, produce executive dashboards and reports, assess contractor performance, and feed lessons-learned into CAPA and process improvements.

Lead strategy, development, commercialization and lifecycle management of indicative pricing and market data products for capital markets across APAC. Define roadmap, drive revenue and P&L, partner with broking, engineering, analytics and sales, ensure methodology and data governance, engage clients and partners, and mentor product teams to deliver market-leading data and analytics solutions.