Top Data Jobs in Singapore

The Staff Data Scientist will lead the technical strategy for payments optimization, implementing advanced algorithms and collaborating with cross-functional teams to enhance payment performance and product adoption.

Intern will apply data analytics and AI modeling to wet etch and clean processes, focusing on process optimization and technology readiness, while developing technical skills and working on experiments.

As an intern, apply data analytics and machine learning to analyze semiconductor data, build models, and communicate insights to teams.

Lead the growth and performance of Airbnb's Homes business in Southeast Asia, managing teams to expand quality supply and enhance guest experiences. Collaborate cross-functionally to ensure market success and monitor business performance against KPIs.

As a Senior Data Scientist, you'll define and execute roadmaps, partner with IT for system management, design scheduling logic, develop solutions in C#, Python, and SQL, and communicate strategic recommendations to leadership while tracking KPIs.

As a Senior Data Engineer, you will design and implement data models, manage ETL pipelines, enforce data governance, and integrate AI practices.

The Staff Data Scientist will design experiments, improve payment products, build measurement frameworks, and mentor junior data scientists at Airwallex.

As a Data Science Engineer, you will analyze large datasets, develop predictive models, and work collaboratively to enhance data tools and processes.

The role involves managing AI system reviews, conducting risk assessments, ensuring compliance, and collaborating with teams to enhance AI governance and reporting processes.

The Data Scientist will analyze big data, develop software solutions, identify insights, and enhance products/services through data-driven decisions.

The program develops skills in warehouse operations, focusing on GMP compliance, continuous improvement, SOP updates, and master data management for biopharmaceuticals.

Drive labor productivity through program management, data analysis, automation, and AI methodologies to enhance operational efficiency and reduce labor hours.

Lead Prudential's AI Lab, driving development of AI solutions, managing sandbox operations, overseeing product quality, mentoring teams, and engaging with external AI talent.

Oversee strategy and architecture of data and AI platforms, resolving challenges, promoting best practices, and mentoring the team.

The Principal Architect will design the data, knowledge, and skills layers for a data platform, ensuring high quality data management and compliance while enabling AI capabilities.

The Manager, FP&A Data oversees financial data maintenance and builds infrastructure for transforming raw data into strategic insights, utilizing SQL, Python, and AI-driven solutions to automate processes and enhance data governance.

The Senior Data Scientist will analyze complex data sets, apply statistical techniques, and collaborate with teams to influence product strategy and improve business outcomes.

The Staff Data Platform Engineer will oversee the strategy, architecture, development, and operations of data and AI platforms, mentor a team, and advocate for best practices in data management and governance.

The Managing Principal will lead data projects, define client data strategies, conduct capability assessments, and influence data-driven culture in financial services.

The role involves leading BIO initiatives, collaborating with sales teams, enabling digital capabilities, and engaging stakeholders to enhance agent productivity and business outcomes.

Manage data provisioning and enablement by collaborating with business units to provision datasets into playpens, maintain workflows, ensure governance and secure data movement, monitor usage, onboard users, document lineage/configurations, troubleshoot access issues, and foster stakeholder relationships to support self-service data exploration and analytics.

The Data Engineer is responsible for designing and maintaining scalable data systems, building data pipelines, and collaborating with teams to support analytics and AI use cases.

Develop and deploy AI/ML and generative-AI solutions: collaborate with stakeholders, research methods, perform data wrangling and feature engineering, maintain deployed models/assistants, build backend APIs and frontend interfaces, document products and fix security issues.

Design, build, and maintain large-scale batch and real-time data pipelines, ETL/ELT processes, and data stores (data lakes, marts, warehouses). Perform data extraction/cleaning (including web scraping), integrate data silos, develop backend APIs, and collaborate with cross-functional teams in an Agile CI/CD environment.

Support design, maintenance, and monitoring of data pipelines and platforms. Troubleshoot system and data issues, help define technical requirements, collaborate with cloud/operations for performance and capacity planning, and participate in reliability and data quality improvements.