Top Data Jobs in Singapore

The Network Technology Sales Specialist engages with clients, identifies opportunities, presents solutions, manages sales processes, and fosters relationships with senior executives to drive growth for NTT DATA.

Embed with strategic customers to design, deploy, and operate large-scale distributed storage and AI infrastructure. Debug performance and networking issues, write code and automation, collaborate with customer engineers, and translate operational requirements into product improvements to ensure successful production deployments.

The Control and Metrics External Data Analyst will manage external data usage, oversee external data initiatives, and support the Chief Data Officer in implementing the Bank's data strategy.

This role involves designing and developing AIML/GenAI solutions, collaborating with engineering teams, and translating business needs into AI-driven solutions.

Lead pricing-focused data science for on-demand services: translate business problems into ML solutions, own full ML lifecycle, improve dynamic pricing using econometrics and causal inference, design experiments, monitor models, and communicate results to stakeholders.

Lead end-to-end delivery of data, analytics, and AI projects on GCP. Manage scope, timelines, risks, cross-functional teams, Agile delivery, stakeholder communication, and governance to ensure solutions meet business objectives.

Lead design and implement enterprise data integrations and movement across systems. Define data contracts, map/transform data, support GenAI data preparation, coordinate deliveries, troubleshoot integrations, and document interfaces while working across platform, application, infrastructure, security teams.

The Technical Services Systems Integration Specialist provides technical support, engages with clients, escalates issues, and mentors junior engineers while focusing on technical implementations across multiple technologies.

Own data quality and root-cause analysis for prediction issues: detect anomalies, trace sources, fix processes, automate QA/reporting with Python and SQL, maintain dashboards, and partner with Data Science, Engineering, Product, and Commercial teams to improve prediction performance and customer-facing analytics.

Support data integrations and quality by checking ingested/system-generated data for anomalies, building and running QA checks and automations with Python and SQL, assisting on customer data queries and dashboards, and documenting findings to improve prediction reliability.

The Research Scientist will conduct innovative research in cloud computing and distributed systems, developing algorithms to optimize performance and efficiency through machine learning techniques.

The Visiting Professor will teach, conduct research, supervise graduate students, and mentor junior faculty while maintaining high scholarly standards and international visibility.

The Research Associate will work on geometric optimization in learning and robotics, including algorithm design and scientific reporting.

Lead data science initiatives, including project scoping, model development, and team training. Drive impactful data-driven business decisions.

Develop and implement statistical models for data analysis, collaborate with teams for process improvement, and present findings to management. Stay updated on data science and machine learning advancements.

Lead marketing measurement: own attribution, incrementality testing, and media mix modeling. Design and analyze experiments, build repeatable templates and self-serve analytics, translate results into budget and growth recommendations, ensure data integrity, and embed AI tools into analysis workflows to measure pipeline and revenue impact.

Design, train, evaluate and deploy machine learning and AI models. Build data pipelines, preprocess data, run EDA, optimise algorithms, deploy models to production (cloud/APIs/containers), monitor performance, document models, and collaborate with cross-functional teams on AI prototypes and production solutions.

Lead global data engineering for wealth management: define roadmap, design scalable pipelines, oversee data lakes/warehouses, select technologies, optimize performance, enforce data governance, and manage a distributed engineering team to deliver high-quality financial data solutions.

Support, design, and optimize LAN, WAN, data center, and cloud network infrastructure. Configure and manage routers, switches, firewalls, load balancers, and wireless systems. Troubleshoot network issues, analyze traffic, implement security controls (VPN, firewall rules, IDS/IPS), monitor performance, create documentation, and contribute to migrations, upgrades, and network projects alongside cross-functional teams.

The Forward-Deployed Data Analyst will engage with African Ministries of Health, build data management solutions, develop dashboards, and support public health decision-making.

The Data Engineer designs and maintains data pipelines and systems, transforming raw data into insights by collaborating with project teams and utilizing various data processing tools.

The Senior Sales Engineer assists customers with technical evaluations, develops sales strategies, and demonstrates expertise in storage products while supporting the sales team and its growth.

Lead early-stage technical development for APAC data center projects: perform site feasibility and due diligence, develop conceptual engineering and layouts, assess power and utility options, estimate CAPEX and schedules, manage stakeholder and authority engagement, identify risks and mitigations, and support transition to design and construction teams while aligning technical solutions with commercial strategy.

Design, build and operate scalable Databricks/PySpark data pipelines to ingest, transform and validate financial vendor data into production-ready datasets, partnering with product and client teams to meet quality and timeline requirements.

Build and deploy data processing pipelines (batch and real-time), clean and extract information, calibrate fraud detection models, collaborate with clients, and conduct R&D on machine learning, NLP, and image analysis to drive product innovation.