Top Data Jobs in Singapore

Lead the design, development, and delivery of AI and GenAI solutions across business domains. Act as an AI Product Owner, translating business challenges into scalable solutions, managing cross-functional delivery squads, and measuring adoption and business value. Develop machine learning, LLM, RAG, agentic AI, orchestration, and governance capabilities while mentoring technical teams and advancing reusable AI standards and assets.

Develop and support batch and streaming data pipelines, data models, ingestion workflows, orchestration, cloud infrastructure, and backend services for banking data platforms. The role also supports AI knowledge bases, vector database pipelines, embeddings, document processing, RAG workflows, and semantic search. Responsibilities include monitoring data quality, troubleshooting pipeline issues, participating in testing and code reviews, and collaborating with engineering, AI, and business teams.

Designs and develops secure, scalable client solutions across cloud and on-premises environments. Responsibilities include gathering requirements, evaluating architectures, creating technical specifications and roadmaps, developing proofs of concept, integrating infrastructure and applications, supporting technical changes, consulting with clients, and contributing to go-to-market services.

Build and maintain production machine learning models and AI products for player personalization, recommendation, propensity scoring, and Next Best Action systems. Collaborate with engineers, analysts, and product stakeholders to translate business needs into pragmatic solutions, integrate models into production, and expand AI-driven player engagement capabilities. Contribute to AI agent architectures, automation workflows, and the roadmap for new ML product opportunities.

Build and maintain ML-ready pipelines for experimental engineering, sensor, and operational data. Responsibilities include feature engineering, data quality monitoring, dataset versioning and lineage, drift detection, data contracts, governance, sensor streaming ingestion, synthetic data infrastructure, and MLOps data-layer components such as feature stores and training dataset registries. The role requires strong Python, SQL, pipeline design, and foundational understanding of ML data lifecycles.

Develop multilingual LLMs for Bahasa Indonesia and regional languages by creating high-quality datasets, performing annotation, preprocessing, model training, evaluation, fine-tuning, and alignment. Ensure data quality, language accuracy, and contextual relevance while collaborating with product and engineering teams to deploy safe, reliable AI features. Improve annotation workflows, document technical solutions, and identify impactful AI use cases.

Manages and grows public-sector client relationships, improves satisfaction and retention, identifies expansion opportunities, and drives revenue and margin targets. Develops account strategies, manages sales pipelines and forecasts in Salesforce, coordinates global teams and partners, addresses client issues, and aligns stakeholders around tailored technology solutions throughout the buying lifecycle.

Leads Vantage’s APAC sustainability strategy, embedding sustainability across development, construction, procurement, operations, and business decisions. Advises executives on ESG risks and opportunities, regulatory and climate issues, stakeholder engagement, customer sustainability needs, and sustainable supply chains. Partners with global sustainability, public policy, communications, sales, and engineering teams to deliver regional programs, reporting, training, data quality, and external engagement. The role requires influencing multinational, cross-functional teams and integrating sustainability into large capital projects.

Develop and deploy deep learning models for computer vision, voice, and text processing. Responsibilities include data preprocessing, model training and optimization, GPU-based deployment, performance evaluation, unit testing, documentation, and production scaling. The role involves translating business requirements into technical solutions, collaborating with engineering teams, and delivering AI systems for KYC and other financial products.

Lead application and systems design, development, and deployment; collaborate with stakeholders to translate business needs into technical solutions; manage and mentor developers; ensure technology standards compliance; and troubleshoot technical issues. The role requires strong application development expertise, leadership, communication, strategic thinking, and customer focus within a banking technology environment.

Conduct technology scans and proof-of-concepts, preprocess data, engineer features, build machine learning models, and present systems to management and users. Potential projects include statistics, machine learning, data visualization, human language technologies, and graph analytics. Interns work closely with mentors to meet project requirements.

Undergraduate data engineering interns will manipulate high-volume streaming data, design databases, conduct technology scans and proof-of-concepts, acquire and query data, develop and test systems, and present solutions. Potential projects include DPI acceleration using Snort and Regex, PCAP search, and KSQL real-time stream processing.

Undergraduate interns will research technologies for efficient big data exploration, then design and build visualization or data-processing components for a Jupyter- and Spark-based analytical platform. The project can emphasize modern frontend development or data science, with opportunities to test solutions at scale.

Design, build, and maintain scalable data pipelines, data lakes, and databases; ingest and map customer financial datasets; monitor pipeline reliability; translate business requirements into data flows and analytical insights to ensure high-quality, usable data.

Support Barclays’ Internal Audit function through data extraction, cleaning, analysis, visualization, and risk-focused insights. Develop analytics for audit testing, automate manual processes, translate audit requirements into use cases, and ensure data integrity and security. Act as a data analytics contact for audit teams, while coaching staff on SQL and Python. Collaborate globally across time zones, manage competing priorities, and advise stakeholders on complex analytical and control-related issues.

Software Engineers are matched confidentially with Dragonfly portfolio companies hiring across crypto and blockchain. Roles may span backend, frontend, full-stack, mobile, infrastructure, data, security, machine learning, and DevOps. Candidates should have software engineering experience and an interest in crypto, blockchain, or open-source technologies. Startup or crypto-native project experience is preferred. Opportunities may be remote, hybrid, or in-person worldwide.

Build and maintain real-time data ingestion systems and warehouses for business logs, user behavior, and operational data. Design and optimize Kafka, Spark, and Flink streaming pipelines, ensuring low latency, reliability, data quality, and high availability. Collaborate with business teams, analysts, and data product managers to deliver metrics, dashboards, and data services. Establish ingestion standards, troubleshoot production issues, govern SLAs, and support cloud-based data warehouse modeling and pipeline operations.

The role involves developing AI-driven solutions for semiconductor engineering, focusing on GenAI systems, data pipelines, and machine learning models while collaborating with cross-functional teams.

Develop and deploy AI and machine learning solutions, including generative AI copilots, recommendation systems, RAG, and agentic AI. Build predictive and generative models using structured and unstructured data, create data-driven visualizations, and collaborate with business stakeholders across domains. The role includes applying modern ML, cloud, MLOps, and real-time data technologies, communicating insights, and potentially managing a team.

Analyzes and profiles customer, KYC, onboarding, and reference data for migration initiatives. Develops source-to-target mappings, transformation rules, validation criteria, and technical documentation. Validates ETL pipelines, executes testing and reconciliation, identifies anomalies, and supports data cleansing and issue resolution. Collaborates with business, compliance, governance, operations, and technology stakeholders to deliver data quality and transformation projects.

Develop and implement Xceptor-based data automation and integration solutions for banking and capital markets workflows. Responsibilities include configuring MessageHub channels, Mail and REST/SOAP API integrations, data transformation, reconciliation, validation, exception handling, and workflow optimization. The role integrates financial platforms and supports trade processing, settlements, reporting, and operational efficiency while collaborating with architects, analysts, and market platform specialists.

Own demand forecasting, supply planning, inventory buffers, wafer starts, assembly loads, and customer on-time delivery for semiconductor products. Collaborate with sales, finance, engineering, marketing, business operations, and external suppliers. Analyze demand and supply data, improve forecast accuracy, manage product transitions, coordinate corrective actions, and oversee vendor and internal project activities.

Manage vulnerability scanning and remediation across on-premises and AWS environments. Maintain the risk register, coordinate risk acceptance and remediation, oversee security signature updates and vendor vulnerability notifications, and perform CVSS-based impact and risk analysis. Prepare leadership dashboards and communicate with technical, business, and customer stakeholders. The role requires managed security services experience, GRC knowledge, ITIL familiarity, and the ability to drive accountability across teams.

Supports an information security program across hybrid on-premises and AWS environments. Manages vulnerability scanning, reporting, remediation tracking, risk registers, risk acceptance documentation, security signature updates, vendor vulnerability notifications, and CVSS-based impact analysis. Prepares leadership dashboards and coordinates with technical and business stakeholders to prioritize remediation and maintain compliance.

Supports the IT PMO by maintaining Power BI dashboards, validating data, analyzing project portfolio trends, and translating findings into management insights. The role improves PMO reporting processes, collaborates on dashboard requirements, and manages the PMO homepage and communications mailbox. It requires strong analytical, communication, organizational, and process-improvement skills, with experience in business intelligence, project reporting, or PMO support.