Top Data Jobs in Singapore

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 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.

Design, develop, deploy, and monitor ML and deep learning solutions including Generative AI and transformer models. Build end-to-end MLOps pipelines, use LLMs, embeddings, vector DBs, and collaborate with data engineering and stakeholders to deliver production AI products and mentor junior staff.

Analyze PB-scale trading, transactional, operational and customer data; build visualizations, ML models and experiments; translate findings into actionable recommendations for trading, operations, product and executives in a fast-paced environment.

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.

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

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.

Lead system and static data setups for new client and fund onboarding, manage conversion activities, validate NAV and shareholder data, standardize processes, liaise with stakeholders, and ensure ISAE/SOC compliance while guiding the client data team.

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.

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.

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.

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.

Data Scientist II role focused on building AI/ML models for optimization. Responsibilities include data analysis, model training, and collaboration across teams to implement AI/ML solutions.

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.

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.

Lead Compliance Data Analytics to research and analyze risk patterns (fraud, account takeover, payment fraud), deploy and iterate rules/models, partner with stakeholders to balance user experience and risk mitigation, drive business-centric analytics and strategic metrics, and build and manage a high-performing compliance analytics team.

Early-career role analyzing PB-scale on-chain, transactional and customer data. Perform data engineering, ETL, querying, build visualizations and ML models, translate insights for teams, manage reporting environment, secure confidential data, and troubleshoot reports/databases.

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.

Early-career role building and evaluating LLM-powered agentic trading systems for crypto markets. Develop pipelines, prompt strategies, retrieval, model evaluations, and ship Python code for production features.

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.