Top Data Jobs in Singapore

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).

Support the Data Science team to design, develop, deploy, and maintain analytics and ML solutions for manufacturing. Responsibilities include data collection/cleansing, EDA, predictive modeling, stakeholder collaboration, production deployment support, and presenting results to leadership.

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 a data insights team to deliver analytics, AI and automation solutions that drive measurable business outcomes. Partner with stakeholders to translate problems into analytical initiatives, manage end-to-end analytics lifecycle, operationalize AI-enabled capabilities, establish KPIs and reporting, and mentor data talent to build organizational analytics maturity.

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 and coordinate health, safety and wellbeing activities for office and data centre construction projects. Monitor compliance, record incidents, perform risk assessments/audits, support legal compliance reviews, train staff, and support global H&S campaigns.

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.

Conduct original research on generative AI and LLMs for crypto/finance, design and run rigorous experiments, build evaluation frameworks, develop post-training and test-time scaling methods, and collaborate with engineers to deploy research into production focused on agent reasoning, alignment, and robustness.

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.

Early-career research role implementing and running experiments on LLM reasoning, post-training alignment, and agentic AI for crypto markets. Tasks include literature synthesis, model implementation (PyTorch/Hugging Face), experiment tracking (Weights & Biases), and collaborating with engineers to translate research into production.

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.

Abstract and enter clinical data from health records, ensure data quality and confidentiality, use EHR/practice management systems and Microsoft Office, troubleshoot basic access/VPN/MFA issues, and collaborate with clinical teams to support operations.

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.

Two-year Talent Accelerator for Senior-level scientists to integrate biology, data, and AI in translational drug discovery. Work in multidisciplinary teams to develop translational models, spatial omics and imaging assays, AI/ML pipelines, and multimodal data integration to identify biomarkers, inform target decisions, and communicate findings to stakeholders.