Top Data Jobs in Singapore

Lead large-scale analytic projects focusing on driving business impact through strategic analysis and machine learning/NLP models in the financial sector.

Lead techno-functional data solutions for Wholesale Banking, Retail, and Global Markets. Gather requirements, design/validate data models (Teradata FSDM, dimensional), profile and map data from core systems, author specifications, collaborate with architects and engineers, execute data validation tests, and provide data-driven insights for strategic decisions.

Lead enterprise data product and Data-as-a-Service strategy, delivery, operationalization, governance, and adoption within a regulated banking environment. Build reusable, governed data products supporting analytics, AI, reporting, and business decision-making. Establish operating models, metadata and lineage standards, quality controls, self-service consumption channels, and Centre of Excellence practices. Partner with senior stakeholders, engineering, technology, governance, risk, and business teams to prioritize use cases, manage delivery, enable AI context, and track measurable value.

Design and build enterprise-scale ingestion frameworks and Lakehouse platforms. Develop reusable Spark/Python components, data models, data products, quality controls, and observability. Support CI/CD, DevOps, Kubernetes-based deployments, and operationalize ML models for AI-driven analytics and risk/fraud use cases in banking.

Lead regional AFC/AML analytics capability: design, build, validate and deploy AML/fraud detection models; guide country analytics teams; ensure model governance, data suitability, and production readiness across stakeholders and regions.

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.

Lead the development and deployment of Generative AI applications, collaborate with teams to deliver business use cases, and enhance data science skills.

Leads Binance’s market data function for its Traditional Finance expansion. Owns strategy, sourcing, licensing, vendor negotiations, integration, governance, entitlements, data quality, lineage, compliance, and budget management. Partners with product, engineering, legal, finance, exchanges, and vendors to build scalable market data infrastructure. Builds and mentors a team while serving as the internal expert on market data and market structure.

Develop and deploy machine learning models that improve e-commerce search relevance, recommendations, product classification, and customer intent understanding. Responsibilities include collecting and preparing large datasets, feature engineering, predictive modeling, validation, testing, and leading work in areas such as NLP, computer vision, information retrieval, and deep learning. The role requires building scalable, reusable machine learning pipelines and collaborating across concurrent projects.

The Technical Product Manager is responsible for product outcomes across the lifecycle, involving product vision, stakeholder engagement, backlog prioritization, and technical leadership.

The Transformation Lead for AI in APAC will manage change and drive adoption of AI tools across the studios, engage stakeholders, and run training programs.

The Enterprise BD Manager will expand and maintain key enterprise accounts, driving growth through strategic relationships and complex solution structures in maritime risk and sustainability.

Wayvia is building a talent pipeline for engineering roles focusing on backend systems, data pipelines, and product engineering. They seek curious and collaborative engineers to connect with and solve future challenges.

The AI Architect will develop AI solutions, support the global AI sandbox, provide technical guidance, and optimize AI products while collaborating with various stakeholders.

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.

Designs, develops, and maintains secure enterprise data pipelines and ETL/ELT processes integrating government and commercial systems. Ensures data quality, performance, availability, and real-time delivery for logistics, mission support, analytics, and operational decision-making. Responsibilities include database and pipeline optimization, cloud migration support, technical documentation, cybersecurity and governance compliance, troubleshooting, stakeholder coordination, operational exercise support, and mentoring junior personnel.

Migrate SQL Server data products and analytical workloads to a modern cloud platform. Redesign legacy SQL, ETL processes, and business logic; build scalable pipelines and analytical models; validate data quality; collaborate with stakeholders; and improve platform reliability, performance, cost efficiency, and AI-assisted data engineering automation.

Supports APAC implementation and operation of MUFG’s Data Governance framework. Oversees data quality, lineage, metadata, data dictionaries, key data elements, controls, reporting, risk remediation, audits, and regulatory requirements. Advises senior stakeholders across business, compliance, operations, technology, and risk; leads governance workstreams for transformations and system changes; facilitates regional forums; and mentors junior team members. Drives governance maturity, process improvements, automation, and adoption of data management standards.

Supports APAC data governance and data quality management activities across banking operations. Responsibilities include maintaining governance documentation, coordinating working groups, monitoring and analyzing data quality, investigating exceptions, tracking remediation, preparing management reports, and engaging regional and global stakeholders. The role also contributes to process improvement, reporting automation, testing, and AI-enabled initiatives.

Develop advanced AI, machine learning, forecasting, optimization, control, and predictive analytics solutions for building automation and energy management. Build mathematical models, simulations, digital twins, and scalable microservices; analyze industrial IoT data; and deploy solutions to cloud and edge environments. Collaborate with architects and business teams to integrate data-driven capabilities into products, identify growth opportunities, communicate customer value, and promote data science best practices. Mentor engineers and support globally distributed teams.

Develops advanced AI, machine learning, forecasting, optimization, control algorithms, mathematical models, simulations, digital twins, and predictive analytics for building automation and energy management. Analyzes industrial IoT data, deploys scalable machine learning solutions to cloud and edge environments, integrates algorithms into customer-facing platforms, mentors engineers, and communicates data-driven opportunities and outcomes to business teams.

Analyze sales channels, business performance, revenue, and acquisition trends; build dashboards and reports; design and calculate sales incentive programs; monitor targets; identify optimization opportunities; and present actionable insights to Sales, HR, and other stakeholders. The role requires cross-functional collaboration, banking industry knowledge, and proficiency in analytics, programming, visualization, and reporting tools.

Own analytical quality for a global manufacturing Control Tower, translating operational data into KPIs, forecasts, scenarios, early-warning signals, performance narratives, and recommendations. Frame complex decisions, apply statistics, forecasting, machine learning, and AI, validate models, monitor performance and data quality, and lead analytical workstreams with cross-functional stakeholders. Build prototypes using Python, SQL, R, BI tools, and cloud technologies while communicating insights and limitations to senior leaders.

Drive new business and expand existing accounts by defining sales strategies, developing pipeline (cold calling, email campaigns), managing end-to-end sales processes, coordinating vendors and inventory, maintaining sales reporting and forecasting, and sustaining vendor and partner relationships.

Develop Green AI technologies focused on efficient machine learning, large language models, model optimization, parameter-efficient fine-tuning, retrieval-augmented generation, prompt engineering, and efficient inference. Conduct experiments, benchmark algorithms, analyze performance, contribute to research publications, and collaborate with multidisciplinary teams to translate research into deployable sustainable computing solutions.