Top Data Jobs in Singapore

The Software Engineer for Data Infrastructure & Acquisition at Speechify will enhance data collection, manage infrastructures, and work with AI scientists to develop large-scale datasets.

Lead analytics to improve player experience, engagement, retention, and monetization. Analyze player lifecycle, run cohort and funnel analyses, design and evaluate A/B tests, build dashboards, define product metrics, investigate KPI changes, and partner with product, marketing, engineering, and data teams to deliver data-driven recommendations and improve data quality.

Support development and implementation of sparse boosting methods for high-dimensional spatial autoregressive models. Perform simulation studies, computational optimization, real-data applications, and prepare reproducible code, reports, presentations, and manuscripts while collaborating with the PI and partners to meet project milestones.

The Senior Data Scientist leads the design and development of machine learning models in healthcare, collaborating with cross-functional teams to deliver impactful insights and compliance.

As an Analyst in Data Science, you'll develop AI/ML solutions, collaborate across teams, and enhance customer experience through innovation. Responsibilities include coding, prototyping, and optimizing algorithms for business challenges.

Plan and execute end-to-end data transformation and migration for large, complex datasets. Lead extraction, validation, reconciliation, mock runs, trial loads, and final cutover while ensuring traceability, audit compliance, and database performance in high-scrutiny government-linked environments.

The role focuses on driving revenue growth through AI-driven solutions and technology sales, involving customer engagement and collaboration with the Salesforce team.

Lead technical strategy with channel partners across ASEAN to design, validate, and scale Microsoft Cloud and Data & AI solutions. Drive offer development, run workshops and POCs, enable specializations, and translate technical work into repeatable, revenue-generating partner services aligned to Microsoft Cloud and AI priorities.

Lead development and implementation of enterprise data security standards, frameworks, and tooling (e.g., DSPM). Create playbooks and training, validate implementations, collaborate with business and technical teams, industrialise data security practices, and drive cultural change and compliance with data regulations across the organisation.

Analyze large-scale on-chain data to detect anomalous transactions, develop detection mechanisms and risk monitoring frameworks, apply supervised and unsupervised ML, identify malicious accounts via community-discovery algorithms, and design integrated on-chain/off-chain prevention and control 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 data management strategies, lead process improvements, support MDM implementations, create Power BI/Excel reports, maintain data lineage/integration, and collaborate with Sales, IT and compliance to resolve data issues and improve data quality.

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.

Lead design and delivery of secure, scalable enterprise data platforms and pipelines. Provide technical leadership on architecture, ETL/ELT, streaming, data modelling, automation, and reliability. Partner with business and risk stakeholders to enable data-driven information risk monitoring, analytics, reporting, and secure-by-design practices to support governance and regulatory compliance.

Lead end-to-end development and productionization of predictive, prescriptive, and agentic AI analytics across commercial, marketing, finance, and franchise domains. Build scalable ML/LLM solutions, implement RAG and orchestration, partner with stakeholders, and drive adoption and business value through analytics products and MLOps practices.

Lead analytics for quick commerce growth across markets: design causal impact and ROI measurement, build BigQuery/dbt SQL models, produce dashboards and agentic AI solutions, influence senior stakeholders, and mentor junior analysts.

Design, deploy, and maintain highly available Kubernetes clusters and GitOps workflows. Build CI/CD pipelines, implement IaC, monitoring, and SRE practices (SLIs/SLOs, error budgets). Lead incident response and automation to reduce toil while collaborating with development and data teams.

Lead application of data science, machine learning and generative AI to drive SME customer lifecycle outcomes. Translate business problems into models, build and deploy scalable production ML/AI solutions, partner with stakeholders and data engineering, monitor model performance, and promote responsible AI and MLOps best practices.

Lead functional business analysis for enterprise KYC/AML capabilities across Group Technology & Ops. Manage stakeholder relationships, define capabilities, translate business requirements into functional and non-functional requirements, oversee testing and scope control, support deployments and post-go-live knowledge transfer, and lead and develop a team of functional business analysts.

Assist in building and maintaining data ingestion pipelines and storage for AI workflows. Implement deployment, security, and monitoring for applications; collaborate with stakeholders and design teams; test and validate data verification and AI workflows; document solutions and follow best practices while continuously learning new tools.

Support the AI team to build generative AI and computer vision solutions: code in Python, explore and analyze datasets, identify patterns, report findings, and implement models using PyTorch, TensorFlow, scikit-learn, and pandas.

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.