Top Data Jobs in Singapore

Embed security controls across the SDLC and ensure secure AWS deployments by performing IaC (Terraform) security reviews, CI/CD/GitLab pipeline security, AWS architecture assessments, vulnerability and open-source dependency reviews, compliance and governance assessments, remediation tracking, and advisory support to DevOps and cloud engineering teams.

Design, build, and maintain scalable data pipelines and ETL processes. Ensure data quality, lead data migrations and processing, advise on data architecture, optimize pipelines, shape best practices, collaborate across teams, and lead stakeholder communications to solve complex data challenges.

Design, develop, and maintain scalable data solutions and pipelines. Ensure data quality, lead ETL/migration efforts, provide architecture and optimization guidance, collaborate with cross-functional teams, and influence data strategy and best practices.

Design, build and operate enterprise-scale data and analytics platforms on GCP. Lead architecture, reliability and incident response for BigQuery/Dataproc/Spark workloads, implement IaC and CI/CD, drive SRE/observability, optimize performance and cost, mentor engineers and enforce security and operational best practices.

Own end-to-end robotics data collection: translate research needs into collection protocols, run multi-site collection operations, maintain rigs and pipelines, define KPIs, diagnose data quality, and align researchers, engineers, and operators to deliver training-ready datasets.

Manage complex, high-risk document and data processing for account servicing, reconciliations, exceptions, vendor coordination, and regulatory/audit support. Serve as SME, lead controls and quality checks, perform root cause analysis, support continuous improvement, and provide backup team lead coverage.

Perform end-to-end product and customer analytics: build dashboards, run A/B tests and segmentation, develop statistical and predictive models, design DataMart architecture, lead campaign and leads management, collaborate with stakeholders, and translate insights into data-driven strategies to optimize product performance and customer outcomes.

Lead and deliver Data & AI projects by designing and maintaining scalable data pipelines, ETL processes, and big-data architectures on AWS. Support SIT/UAT and production, troubleshoot issues, collaborate with stakeholders and vendors, ensure data security/compliance, and develop analytics tools to provide business insights.

Perform document retrieval, data entry, control checks, and processing of customer communications and PIN requests. Monitor exceptions, liaise with internal teams and vendors, support reporting and audits, validate scanned records, and participate in UAT and ad-hoc process improvements while ensuring compliance with SOPs and SLAs.

Lead digital, data, and AI adoption by partnering with business leaders, designing enablement and change programs, supporting pilots, measuring adoption KPIs, and advising stakeholders to scale user-centric analytics and AI solutions.

Lead causal modeling and optimization for promotional spend across mobility, delivery, and logistics. Own end-to-end uplift and incrementality modelling, experiment and quasi-experiment design, heterogeneous treatment effect estimation, and budget-constrained allocation. Mentor data scientists, productionize models at scale, partner with product and engineering, and translate model outputs into business budget decisions.

Lead technical consulting teams for pre-sales, delivery, maintenance and offshore vendor management for customer communication and enterprise content management solutions. Own technical solutioning for bids, ensure project delivery and support SLAs, manage vendor operations, coach staff, track operational metrics, and drive continuous improvement across professional services.

Serve as ASOs single front door for Operations demands across Asia, translating business needs into prioritized initiatives, managing demand pipeline, shaping improvement using AI/data/APIs, and coordinating stakeholders to deliver operational efficiency, compliance, and value realization.

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.

Lead architecture, design, and development of a scalable ML and generative AI data platform. Build infrastructure to process structured and video telematics data, support model training and LLM access, implement logging/monitoring, integrate with cloud and Big Data systems, document architectures, support integrations, and mentor engineers.

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.

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.

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.

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

Lead design, delivery, and continuous operation of enterprise data and analytics products. Manage cross-functional teams, stakeholder engagement, product roadmaps, vendor relations, data governance, and drive efficiencies and improvements across analytics platforms.

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.

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.

Collect, analyze, and interpret game data to produce insights for R&D, marketing, and operations; build scalable data pipelines and ML models; collaborate with product managers and engineers; research new ML/AIGC approaches for gaming applications.

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.