Top Data Jobs in Singapore

Lead and manage data migration projects, gathering requirements, coordinating teams, defining data mappings, and ensuring compliance through testing.

Lead data analysis projects, oversee data migration, ensure data quality, and manage project teams while collaborating with stakeholders.

The Cloud Sales Specialist drives sales in Hybrid Cloud solutions, builds relationships with clients, and collaborates with internal teams to meet client needs and achieve sales targets.

The Networking Sales Specialist identifies new opportunities, supports the sales process, builds client relationships, and leads conversations to drive business growth.

The Associate Systems Integration Specialist will learn to manage configurations, installations, and support break/fix events with the TS Systems Integration team.

The Associate Systems Integration Specialist learns to manage configurations, installations, and break/fix events and supports senior engineers during the project lifecycle.

As a Senior Cross-Technology Technical Architect, you will design transformative solutions, support business development, mentor junior architects, and influence sales strategies, ensuring successful implementation for clients.

As a functional business analyst, you will collaborate with teams to gather requirements, propose solutions, and ensure quality deliverables for data and CRM projects in the banking sector.

As a Data Scientist, you'll build machine learning models, enhance search system performance, and collaborate with various teams to improve operational efficiency.

As the Data Analytics Lead, you will develop CoinGecko's analytics strategy, manage data platforms, and lead a team to enhance data culture and governance.

As a Data Engineer at Xtremax, you'll design, build, and maintain data pipelines, collaborate with various teams, and transform data for analytics.

Assist in developing analytical and machine learning models to improve semiconductor manufacturing performance, focusing on data extraction, processing, and analysis.

The intern will apply data science, statistics, and machine learning in semiconductor process development, focusing on data analysis and predictive modeling for process improvement.

Analyze customer service performance, validate customer service signals, build dashboards, and partner with stakeholders for data-informed decisions.

Analyze DTC & sales performance, design measurement plans, maintain dashboards, and collaborate with teams to drive data-informed decisions.

Assist in translating business cases into technical solutions utilizing various technologies. Support data warehouse design, address performance issues, and contribute to data management standards.

As a Senior Product Data Analyst, you will drive data-backed decision-making, analyze on-chain and off-chain data to optimize product performance, and enhance user experience through experimentation.

The Visualization Engineer will develop interactive dashboards and applications, analyze data for insights, manage visualization projects, and collaborate with engineering teams.

The Transaction Director leads a team in managing real estate transactions for data centers across APAC, ensuring successful site acquisitions and collaboration with stakeholders.

As a Data Scientist, you'll analyze large datasets using statistical modeling and machine learning. Responsibilities include developing software for data cleansing, evaluating diverse data sources, and collaborating with cross-functional teams.

Assist in research and development of machine learning algorithms, statistical analysis, user behavior mining, and improving data pipelines as part of an intern role at Lightspeed Studios.

The role involves advising on data privacy and protection, ensuring compliance with regulations, managing privacy policies, and collaborating on data privacy issues and contract reviews.

The Data Processing Specialist will assist in records management and data privacy efforts to support customer needs at Iron Mountain.

Interns will utilize LLMs to summarize and compare regulatory texts, as well as build data augmentation pipelines for fraud models.

The role requires designing and developing data infrastructure, utilizing Hadoop and Spark in large-scale environments, while also leveraging containerization and automation tools.