Top Data & Analytics Jobs in Singapore

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 Senior Data Scientist will partner with executives and teams to leverage data, enhance forecasting, and build data products, utilizing AI insights for business efficiency.

The Growth Manager will lead growth metrics, enhance customer insights with data science, and drive actionable growth strategies based on analysis. Responsibilities include overseeing KPIs, building intelligence models, and translating complex analytics into measurable business outcomes.

The Data Ops Associate will design and manage data pipelines and reporting systems, focusing on automation, data quality, and compliance, while collaborating with global teams to meet business and regulatory needs.

The Associate, Credit Risk Operations will conduct credit risk reviews, assess merchant credibility, provide recommendations, and lead process improvements to mitigate risks while facilitating growth.

The Senior Data Scientist will analyze risk, develop financial crime detection solutions, and optimize risk strategies using advanced analytics and machine learning.

As a Senior Data Scientist in Analytics (Risk & Compliance), you will lead analytics projects, ensure robust data foundations, and collaborate cross-functionally to improve regulatory compliance and risk oversight.

Design and evolve a governed data, knowledge, and skills platform for analytics and AI agents. Lead data modelling, regional data localisation, semantic layer and metric-store design, agent APIs, and Governance-as-Code to ensure quality, lineage, and compliance across global Databricks environments.

Design and implement scalable data models, manage ETL pipelines, contribute to data governance, and understand AI integration for data engineering.