Top Data Jobs in Singapore

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.

Support Singapore laboratory operations by developing and maintaining digital tools (Power BI/Power Apps), performing data analysis to improve equipment calibration, maintenance, and inventory processes. Manage end-to-end inventory activities, procurement, receiving, storage, archival and disposal of samples/consumables. Ensure 5S, safety and cGMP compliance, coordinate vendor logistics and present findings to Quality leadership to drive quality and productivity improvements.

Lead R&D of AI/ML algorithms for multimodal medical imaging, digital pathology, spatial-omics and molecular data to discover deployable biomarker solutions. Collaborate cross-functionally, build reusable ML pipelines, partner with external institutions, present findings, and author technical proposals and reports to support drug development.

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.

Design, develop, and manage large-scale search and content recommendation systems. Apply ML-based personalization to improve content matching and distribution. Lead core recommendation module development, define success metrics, and collaborate with content, product, and business teams to drive AI product upgrades and better user and business outcomes.

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.

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 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.

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.

Develop and optimize marketing-focused algorithmic models (CTR/CVR, LTV, attribution, uplift), design lifecycle strategies for acquisition/retention, validate via A/B testing and causal inference, and collaborate with data/product/operations to deploy models into marketing systems to drive growth.

Early-career data scientist role to analyze user and content data, build metrics, design recommendation strategies (recall, ranking, cold-start, diversity), run A/B tests, evaluate experiments, explore LLM/multimodal applications, and improve data pipelines and feature logging.

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.

Ensure accuracy, consistency, and quality of master data across commercial systems. Manage master data lifecycle, enforce data governance and GDPR compliance, implement MDM systems, create Power BI/Excel reports, develop data quality controls, maintain business glossary and data lineage, and collaborate with Sales, IT, and compliance teams.

Ensure accuracy, consistency and quality of commercial master data across systems. Implement data governance and GDPR-compliant processes, support MDM implementations, produce Power BI/Excel reports, manage data lineage/integration, and drive data quality improvements in collaboration with Sales, IT, and compliance teams.

Build and maintain user tagging and profiling systems, analyze large-scale behavior data, perform feature engineering and exploratory analysis, support cross-functional teams for segmentation, monitor tag effectiveness, detect anomalies and fraud patterns, and improve data methodologies to enable risk control and personalized services.