Top Data Science Jobs in Singapore

The Research Associate will work on geometric optimization in learning and robotics, including algorithm design and scientific reporting.

Lead data science initiatives, including project scoping, model development, and team training. Drive impactful data-driven business decisions.

This role involves leading strategic consulting engagements in financial services, managing projects, business development, and mentoring junior consultants while driving Sia's growth in the sector.

Lead and manage a team of Partner Solutions Architects, providing technical guidance to consultative partners, driving customer success, and enhancing partner engagement with the Databricks platform.

The Head of Data Science will lead the data science team across Southeast Asia, focusing on credit risk model development, strategic collaboration, and shaping the machine learning roadmap.

Lead the implementation and maintenance of AI agent applications, enhance performance, manage lifecycle, and ensure compliance with regulatory standards while coordinating cross-functional teams for operational excellence.

Lead global technical recruiting across engineering, product, data, AI/ML, infrastructure and security. Own end-to-end hiring, sourcing strategies, talent mapping, stakeholder partnership, ATS/reporting, and mentor junior recruiters to build scalable TA processes and pipelines.

The Principal Expert leads the data science strategy for MSAT, establishes best practices, delivers high-impact initiatives, and mentors teams in a regulated environment.

The Director of AI is responsible for solving complex AI challenges, exceeding client expectations, leading AI teams, and fostering ethical AI practices. They will create thought leadership and manage AI solutions from conception to commercialization while building client relationships and partnerships.

Own net-new enterprise logo acquisition in Singapore: build territory strategy, run discovery calls and demos, create pipeline, engage business and IT stakeholders, close deals to meet quotas, and collaborate with partners and cross-functional teams to accelerate complex, high-value Snowflake AI and data opportunities.

The Senior Executive will manage participant communications, screening, data monitoring, report submissions, and adherence to study protocols in clinical research.

Design, develop, and evaluate AI-driven solutions for sustainable living. Collect and preprocess multimodal datasets, build data pipelines and experiments, analyze model performance, iterate on models, and collaborate on publications, reports, and demonstrations.

Analyze large-scale datasets to identify opportunities and optimize product performance; build dashboards and visualization tools; assist in developing scalable data pipelines to support operations and platform security; and collaborate with product, engineering, and legal teams to turn analyses into actionable business strategies.

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.

Design and build generative and agentic AI solutions and end-to-end ML applications. Analyze structured and unstructured data, develop ML models, deploy pipelines, dashboards and cloud architectures. Advise clients, run workshops, support pre-sales PoCs, and translate business requirements into scalable AI solutions while collaborating with stakeholders.

Design and deliver production-ready AI and data science solutions across CRM, retail, marketing and operations. Build ML models, GenAI/RAG pipelines, feature engineering and training workflows; collaborate with data engineering to deploy, monitor and optimize models; run experiments and measure business impact while ensuring responsible AI, security and governance.

A 12-month graduate programme offering rotations and hands-on projects in Technology or AI & Data Science. Responsibilities include building and deploying software, cloud and infrastructure work, cybersecurity practices, and developing ML/GenAI solutions (LLMs, agents, MLOps). Participants receive structured training, mentoring, and exposure to senior leaders while working on real enterprise problems to deliver scalable, secure, and impactful solutions.

Lead design and delivery of AI-powered automation, Copilot agents, advanced analytics, and monitoring solutions for global Healthcare Compliance. Translate business problems into scalable data-driven solutions, partner with governance and technology teams, and mentor stakeholders while implementing APIs, BI dashboards, process mining, and Cloud-based generative AI capabilities.

Conduct research on vector search and AI methods for sustainability. Develop quantitative sustainability indicators, AI-enabled monitoring frameworks, and data-driven ESG assessment tools. Build data collection/validation/visualization tools, design experiments and statistical models, ensure trustworthy AI, collaborate with multidisciplinary teams, and produce proposals and scientific publications.

Work on data-driven projects to improve WeChat safety strategies: analyze large datasets, build dashboards and visualizations, develop scalable data pipelines to support operations and platform security, and collaborate with product, engineering, and legal teams to turn analytics into actionable strategies.

The Data Science Intern analyzes large datasets, uses machine learning and analytics to solve gaming challenges, and collaborates with teams to drive business strategies.

Build and deploy data processing pipelines (batch and real-time), clean and extract information, calibrate fraud detection models, collaborate with clients, and conduct R&D on machine learning, NLP, and image analysis to drive product innovation.

Work with client teams to frame data needs, analyze marketing/customer/product data, build and deploy ML and generative AI solutions, create dashboards, and support data transformation and enablement across luxury, consumer goods, and retail use cases.

Lead strategy and execution of data analytics and data science across the organisation: build and mentor teams, partner with cross-functional stakeholders, drive data-driven initiatives that improve risk management and business metrics, uplift tooling and capabilities, and ensure data governance and regulatory compliance across markets.

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.