Top Data Jobs in Singapore

Develop machine learning and statistical models for geotechnical laboratory and project datasets; automate QA/QC and anomaly detection; integrate and clean LIMS/LabPro/RFID data; link laboratory, CPT, geophysical and imaging data; produce dashboards and analytics for operations; validate models with domain experts and document methods for the Marine Ground Digital Twin platform.

Design, build and maintain scalable ETL/ELT data pipelines and integrations on Microsoft Fabric and Databricks. Prepare and model data for AI/ML and analytics, ensure data quality, lineage, security and governance, develop connectors/APIs, support CI/CD deployments, monitor pipelines, and document handovers while collaborating with stakeholders and AI/ML engineers.

Lead social media and external communications strategy: consult with partners, craft and project corporate messaging across social channels, oversee analysis of social responses and recommend actions, represent the company to online communities and media, and hire/develop team members to run the function efficiently.

Use large datasets to produce dashboards, reports and visualizations; identify trends and anomalies; perform statistical analysis and predictive modeling; collaborate with business units to translate needs into specifications and resolve data quality issues; communicate findings to non-technical stakeholders.

Lead end-to-end data science initiatives across pay TV, digital products, media sales, and customer lifecycle. Design, deploy, monitor ML/AI solutions (churn, propensity, personalization, recommendation, forecasting), partner with stakeholders, build data pipelines, run experiments (A/B, uplift), mentor teams, and translate analytics into measurable commercial impact.

Design, build, and maintain scalable data pipelines, data lakes, and databases; ingest and map customer financial datasets; monitor pipeline reliability; translate business requirements into data flows and analytical insights to ensure high-quality, usable data.

Lead and execute Vantage's APAC public policy strategy, manage government and regulatory engagement, build and lead a regional policy team, coordinate with internal stakeholders, manage third-party advocates, ensure compliance with lobbying and anti-corruption laws, translate policy risks into business actions, and support sustainable, community-aligned growth across APAC markets.

Provide technical and business application support for wealth data platforms, ensuring stability, performance and SLA adherence. Monitor production systems, perform reconciliations, troubleshoot incidents, coordinate releases, maintain runbooks and contingency plans, and liaise with stakeholders, development teams and vendors. Coach junior analysts and drive stability, efficiency and effectiveness improvements across the support function.

Build and refine underwriting and loss-prediction models using alternative data; develop features and end-to-end credit models; partner with credit, engineering, and leadership; present findings to non-technical stakeholders; operate in a lean, high-growth environment (remote role with occasional travel).

As a Data Scientist in AI Fintech, you will build machine learning models for fraud detection, analyze data, and ensure compliance with regulations.

The role involves owning product feature development, participating in system design, and maintaining software performance in an agile setting.

The Director of APAC Channels drives the Channel GTM strategy, recruits and trains teams, manages partnerships, and monitors performance to accelerate growth.

Join the Financial Services team as an intern to support banking projects through research, analysis, and collaboration with consultants.

Lead a unified data and experimentation framework across the company, engaging with core business lines to support data-driven decision-making, while ensuring data quality and governance.

The AI Solutions Architect will lead AI strategy, design AI architectures, assess AI opportunities, build AI solutions, and ensure compliance with governance frameworks.

Design and lead end-to-end enterprise data and GenAI architectures, drive cloud migration/modernization, define GenAI/Copilot/agentic patterns (RAG, embeddings, vector search), establish MLOps/LLMOps and governance, ensure Responsible AI and security, and act as trusted technical advisor across presales through production.

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.

Design and build generative and agentic AI solutions and end-to-end ML applications. Analyze structured and unstructured data, develop ML models, deploy pipelines, dashboards and cloud architectures. Advise clients, run workshops, support pre-sales PoCs, and translate business requirements into scalable AI solutions while collaborating with stakeholders.

Lead full‑lifecycle cost management for Civil, Structural & Architectural packages on a large data centre. Prepare cost estimates and plans, advise on design and construction methods, manage tendering and procurement, control post‑contract changes and payments, produce cost reports and forecasts, support final accounts, and coordinate stakeholders to manage cost risks and ensure financial governance.

Develop, implement and maintain machine-learning credit risk models for consumer, small business and wholesale portfolios. Monitor and back-test model performance, support model governance and validation, engage auditors/regulators, and collaborate with stakeholders to apply model outputs to decisioning, allowance and capital assessment.

The role involves designing and maintaining data pipelines, collaborating with stakeholders, ensuring compliance with regulations, and mentoring junior members. Requires data engineering and science expertise.

The Data Engineer 2 will design, develop, and maintain data pipelines, frameworks, and models, ensuring data quality and governance while collaborating with scientists and analysts.

The Data Scientist will identify new data sets, build processes for data collection, analyze data for potential applications, and research alpha signals for portfolio managers.

The Data Analyst will analyze financial datasets, create data pipelines, engage with vendors, automate data checks, and support investment teams.

Design, develop, and maintain ELT/ETL Snowflake data warehouse solutions; implement data standards, CI/CD, monitoring, and production support; collaborate with product, business, and vendors; mentor junior developers and improve data engineering practices.