Top Data Jobs in Singapore

The role involves leading data analytics initiatives to improve yield and quality, developing algorithms, enhancing data infrastructure, and collaborating with cross-functional teams to drive innovation in HBM product engineering.

Lead advanced data analytics and ML initiatives to improve yield, quality, and reliability for HBM products. Develop ML/DL models, build data infrastructure, integrate solutions into disposition workflows, mentor team members, and collaborate cross-functionally to optimize KPIs including quality, cost, cycle time, and scale.

Design and deploy computer vision and deep learning models (CNN, LSTM, transformers) for industrial inspection and anomaly detection; extract, clean, and analyze large multimodal datasets; implement MLOps (MLflow, Airflow, Docker) for production deployments; collaborate across engineering, operations, and quality teams; mentor engineers and contribute research outputs and technical documentation.

Design, build, and ship agentic AI applications that answer business questions over governed data. Implement RAG, NL-to-query, tool/function calling, and evaluation/guardrails. Partner with data teams on metrics, models, pipelines, and apply strong data governance and security for financial services.

Develop and deploy optimization, simulation, and ML models to improve semiconductor factory capacity, throughput, and cycle time. Partner with cross-functional manufacturing and engineering teams to analyze constraints, run scenario analyses, and deliver data-driven recommendations integrated into production pipelines and decision-support tools.

Lead credit risk analytics for business lending: monitor portfolio performance, identify emerging risks, support portfolio-level credit strategies, prepare reports and dashboards, collaborate with operations and product, contribute to stress testing, regulatory reporting, and governance.

Drive data science for Coinbase consumer products by analyzing ambiguous business problems, defining metrics, building experimentation and causal frameworks, developing advanced models, maintaining ETL pipelines, and translating insights into product strategy. The role requires SQL and Python expertise, statistical rigor, data visualization, stakeholder influence, code reviews, and responsible use of generative AI tools.

Lead design and implementation of cloud DevOps strategy for global Data and AI infrastructure. Build observability and detection capabilities, enable self-service tooling for data teams, manage scalable, secure infrastructure, and align DevOps practices and standards across geographies.

Design and implement smart manufacturing AI solutions for advanced factory scheduling, optimization, and simulation. Build analytics and applications, apply new algorithms, collaborate across global sites, drive benchmarking, and support continuous improvement of production metrics.

Prospect into Singapore public sector organizations through phone, email, social selling, events, and other outbound channels. Research accounts, identify stakeholders, tailor outreach, qualify prospects, and create sales opportunities in partnership with Account Executives and partners. The role focuses on achieving activity, meeting, pipeline, and new-logo targets while engaging technology stakeholders across IT, security, cloud, data, and engineering.

Lead data governance and management consulting engagements for financial services clients. Design governance frameworks, maintain data dictionaries, glossaries, metadata catalogs, lineage, and classification standards, and support data quality, architecture, MDM, and regulatory compliance initiatives. Partner with executives, risk, compliance, technology, and business stakeholders while delivering Agile data transformation programs and governance reporting using enterprise platforms such as Collibra, Informatica, and Microsoft Purview.

Design and implement analytics, simulation, optimization, and digital twin solutions for semiconductor manufacturing. Develop software, models, and AI/LLM-enabled tools to analyze large unstructured data, optimize operations, and communicate insights to product and operations teams while driving global collaboration and continuous improvement.

The Senior Data Scientist will improve semiconductor quality through predictive models and AI solutions, mentor juniors, and communicate insights effectively.

Develop and deploy product-disposition workflows and deviation alert systems using statistical tools and ML/AI to improve yield, reliability, and quality. Build algorithms for data mining, pattern recognition, and wafer/die screening. Collaborate with Fab, design, and quality teams, mentor team members, and drive technical innovation to meet KPIs like quality, cost, cycle time, and scale.

The Data Scientist will optimize semiconductor processes, analyze data, develop visualization tools, and support production through advanced analytics and modeling.

Design, implement, and maintain data-driven processes and analytics solutions. Collect, cleanse, automate, and prepare data from disparate sources. Build KPIs and dashboards, apply statistical and machine learning methods, collaborate with stakeholders, perform testing and deployment, and train users to enable data-driven decision making and process improvements.

As a Computer Vision Engineer, you will develop image processing solutions, apply machine learning techniques, and collaborate on engineering projects to enhance manufacturing innovation.

As a Senior Data Scientist, you'll analyze large datasets using advanced mathematical and statistical methodologies to derive actionable insights and optimize semiconductor operations.

The role focuses on developing product disposition solutions, enhancing yield and reliability through data analysis, and mentoring team members while collaborating across teams.

The IT Engineer (Data Services) is responsible for database system management, performance tuning, compliance, incident resolution, and automation of database operations.

Lead procurement data strategy to enable agentic AI: design agent-embedded governance, define agent-consumable data requirements, build lineage/catalog foundations, establish machine-readable policies and feedback loops, run experiments, and coach cross-functional stakeholders to operationalize master data and data quality at scale.

The role involves developing advanced data analytics solutions for yield and quality improvement in HBM product engineering, collaborating with cross-functional teams and driving innovation in AI and machine learning.

The Data Scientist will analyze big data to develop predictive models and actionable insights, collaborating with various teams to enhance products and services.

Partner with APAC Compliance teams to deliver regulatory reporting, compliance monitoring, risk analytics, and assurance reporting. Build scalable data models, dashboards, and self-service analytics tools while validating regulatory submissions and supporting automated monitoring. Maintain data quality, governance, and documentation, and collaborate with Risk, Compliance, Product, and Engineering stakeholders. The role requires strong SQL and data modeling skills, with opportunities to use dbt, modern data warehouses, data engineering tools, and Python.

Lead Databricks’ enterprise sales organization across Malaysia and Indonesia, managing Enterprise Account Executives and owning team quota attainment. Develop strategic revenue plans, grow consumption among strategic financial services accounts, build executive customer and partner relationships, and translate technical data and AI capabilities into business value. The role requires Bahasa fluency, extensive enterprise software sales leadership, strong Data and AI expertise, hyperscaler relationships, and a proven record of developing high-performing teams.