Top Data Jobs in Singapore

Lead commercialization and regional sales for Mastercard Advanced Analytics to financial institutions across Asia Pacific. Own sales strategy, build multimillion-dollar pipelines, manage complex enterprise deals, engage C-suite stakeholders, and collaborate with product, consulting, and account teams to close and expand strategic contracts.

As Product Manager, you will own the vision and roadmap for Mastercard's Responsible AI and Privacy Enhancing Technologies Toolkit, ensuring product features align with governance, privacy, and regulatory expectations, while driving adoption and product outcomes.

As a Data Science Engineer, you'll analyze big data, develop models, deploy solutions, and communicate insights to improve products and services.

The Engineering Director will lead software engineering teams, set technical direction, ensure product quality, and foster innovation and collaboration.

The role involves leading data analytics initiatives to improve yield and quality, developing algorithms, enhancing data infrastructure, and collaborating with cross-functional teams to drive innovation in HBM product engineering.

Analyze semiconductor manufacturing data to identify yield detractors, build data pipelines, apply statistical and machine learning models for yield improvement, support DOE experiments, and create automated dashboards and reports for engineering stakeholders.

Manage, maintain, and optimize critical database systems (SQL Server, Oracle). Perform installs, patches, backups, access control, monitoring, performance tuning, incident/change/problem management, on-call support, capacity planning, automation, reporting, and collaborate with global teams and site stakeholders.

Design and deploy computer vision and deep learning models (CNN, LSTM, transformers) for industrial inspection and anomaly detection; extract, clean, and analyze large multimodal datasets; implement MLOps (MLflow, Airflow, Docker) for production deployments; collaborate across engineering, operations, and quality teams; mentor engineers and contribute research outputs and technical documentation.

The Enterprise Account Executive, Acquisition role focuses on developing a sales strategy within a territory for new customer acquisition, meeting sales targets, and collaborating with Solutions Architects and Professional Services teams.

The SR Data Scientist will analyze data in semiconductor manufacturing, optimize yields, develop data pipelines, support experiments, and communicate findings using visualization tools.

Design and deploy computer vision and deep learning solutions for manufacturing inspection and monitoring. Extract and clean large datasets, build multimodal AI models, apply MLOps for production deployment, and collaborate with cross-functional teams to translate research into operational systems and documentation.

Support investment teams by acquiring, cleaning, and analyzing diverse datasets to test investment theses. Learn fundamental investor approaches, identify key data drivers and inflection points, and present research findings. Work with existing and new data to generate insights and decision-support tools for sector-focused investment research.

Work with trading, operations, and reporting teams to identify and prioritize data quality and operational issues. Build SQL/Python-based data solutions and dashboards, perform root-cause analyses, implement fixes, and support scaling and documentation while aligning to controls and stakeholder requirements.

The Staff Data Scientist will optimize semiconductor manufacturing processes through data analysis, statistical modeling, and data visualization, collaborating closely with engineering teams.

Design and implement advanced scheduling, optimization, and simulation solutions in manufacturing to improve production metrics and drive innovation.

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.

The role focuses on developing product disposition solutions, enhancing yield and reliability through data analysis, and mentoring team members while collaborating across teams.

Design, build, and ship agentic AI applications that answer business questions over governed data. Implement RAG, NL-to-query, tool/function calling, and evaluation/guardrails. Partner with data teams on metrics, models, pipelines, and apply strong data governance and security for financial services.

Develop and deploy optimization, simulation, and ML models to improve semiconductor factory capacity, throughput, and cycle time. Partner with cross-functional manufacturing and engineering teams to analyze constraints, run scenario analyses, and deliver data-driven recommendations integrated into production pipelines and decision-support tools.

Lead design and deployment of agentic AI for manufacturing planning and operations. Build multi-agent systems combining LLM reasoning and optimization (MIP, heuristics, simulation), integrate agents with data pipelines and enterprise systems, and deliver solutions for capacity planning, production flow optimization, and decision automation. Partner with planning, operations, data engineering, and MLOps teams to translate domain requirements into deployable AI workflows and reusable orchestration frameworks.

Lead credit risk analytics for business lending: monitor portfolio performance, identify emerging risks, support portfolio-level credit strategies, prepare reports and dashboards, collaborate with operations and product, contribute to stress testing, regulatory reporting, and governance.

Lead design and implementation of cloud DevOps strategy for global Data and AI infrastructure. Build observability and detection capabilities, enable self-service tooling for data teams, manage scalable, secure infrastructure, and align DevOps practices and standards across geographies.

The IT Engineer (Data Services) is responsible for managing and optimizing database systems, ensuring data availability, performance, and compliance, while also developing automated solutions and collaborating with site customers.

The role involves ensuring end-to-end performance and power readiness of Data Center SSD programs through technical execution, analysis, and leadership across teams.

Design and implement smart manufacturing AI solutions for advanced factory scheduling, optimization, and simulation. Build analytics and applications, apply new algorithms, collaborate across global sites, drive benchmarking, and support continuous improvement of production metrics.