Top Data Jobs in Singapore

Lead a team in developing scalable data solutions, mentor engineers, manage expectations, and contribute to code. Focus on high-quality software practices.

The Networking Technical Services Systems Integration Specialist provides technical support to clients, documents project specifications, mentors junior staff, and assumes ownership of networking technologies and projects.

Lead and deliver concurrent standard or complex client projects from concept to implementation, manage scope, budget, risks, issues, and stakeholder communications, act as single client contact, support pre-sales, and ensure successful handover to operations.

The role involves providing technical support, engaging with clients, writing documentation, and mentoring junior engineers in Networking implementations.

The Senior Associate Networking Technical Services Specialist is responsible for network installations, troubleshooting, problem resolution, and documenting procedures while developing knowledge in networking technologies.

Lead generation and closure of complex, cross-technology solution sales. Build and maintain C-level client relationships, conduct workshops and presentations, collaborate with sales and pre-sales teams, leverage vendor relationships, craft tailored solutions, forecast opportunities, and meet sales targets while contributing best practices to internal knowledge bases.

Lead data-driven strategies for cross-border payments, manage BI and Data Engineering teams, and enhance business efficiency through data insights.

Analyze blockchain data, creating efficient query solutions and fraud detection methodologies while ensuring data integrity and transforming customer data needs into actionable insights.

Own end-to-end ML solutions to improve driver allocation, surge pricing, and incentives. Translate business problems into models, deploy and monitor production systems, design experiments, apply causal inference, optimization and simulation, and communicate results to cross-functional stakeholders.

The Senior Data Scientist will identify fraud patterns, develop machine learning models, collaborate with technical teams, and provide analytical insights to mitigate risks in crypto transactions.

Design, build, and deploy production-grade ML models (cross-sell, upsell, recommendation, LTV), automate model lifecycles with SageMaker, leverage LLMs for personalization and insight generation, run A/B tests, collaborate with product and engineering, and mentor junior data scientists to drive measurable revenue outcomes.

Responsible for sales results in mid-size and large accounts, developing customer relations, analyzing sales data, and driving innovative products.

As a kdb+ Engineer, you will develop and maintain applications, support project delivery, analyze time-series data, and mentor junior developers.

Lead technical delivery of projects, design kdb+ architectures for time-series data, mentor developers, and drive innovation in kdb+ systems.

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.

As a Lead Data Scientist, you will improve dynamic pricing systems, lead ML projects, collaborate with teams, and analyze data for business impact.

Develop and implement data loss prevention policies, assess data security risks, monitor logs for potential breaches, respond to incidents, collaborate with IT teams, and train employees on data protection best practices.

Design, build, and operationalise large-scale cloud data pipelines (batch and streaming) using Databricks/Snowflake and cloud platforms to support reporting, automated systems and AI/ML teams. Administer cloud data platforms, optimise SQL/storage, implement CI/CD, IaC, containerisation and serverless solutions, and collaborate with clients, partners and internal teams to scale data engineering deployments.

Investigate transaction and financial data to detect anomalies, fraud, and risk exposures. Partner with Finance, Risk, Compliance to frame questions, produce trusted analytics, dashboards, and alerts, and help design and validate AI-driven monitoring and automated reporting. Improve data quality, metric definitions, and support automation of manual checks to ensure reliable financial reporting and risk controls.

Build and maintain end-to-end data pipelines and medallion data lake architectures on Databricks and AWS. Implement data governance with Unity Catalog, ensure data quality, prepare analytics-ready datasets, support basic ML pipelines, and collaborate with stakeholders to meet reporting and BI needs.

Design and lead end-to-end enterprise data and GenAI architectures, drive cloud migration/modernization, define GenAI/Copilot/agentic patterns (RAG, embeddings, vector search), establish MLOps/LLMOps and governance, ensure Responsible AI and security, and act as trusted technical advisor across presales through production.

The Visiting Professor will participate in teaching and research, supervise graduate students, and mentor junior faculty at NTU's College of Computing and Data Science.

Lead end-to-end data science initiatives for commodity trading, focusing on palm production, weather modeling, commodity flows, tanker analytics, and market insights. Build scalable databases, dashboards, reports, alerts, and decision-support tools using large datasets. Partner with traders, researchers, technology teams, and leadership to drive projects from ideation through adoption. Mentor junior data scientists, establish best practices, and translate complex analysis into actionable commercial recommendations.

Design and maintain high-throughput pipelines for large-scale unstructured data processing. Build transformation, enrichment, vector embedding, hybrid retrieval, multimedia analysis, and computer vision capabilities. Ensure data quality, reliability, testing, observability, and performance while collaborating with data scientists, frontend engineers, and product managers to support national security analytics.

Manage physical security for a cluster of data center buildings: develop policies, oversee daily operations and staff, run risk assessments and incident response, manage vendors, budgets, compliance, and security technologies, and deliver regular reporting and training.