Top Data Jobs in Singapore

Manage and expand strategic partnerships across Southeast Asia, Japan, Greater China, and South Korea. Recruit and develop GSIs, SIs, agencies, MSPs, OSPs, and other services partners; create joint business plans; drive co-selling, partner-led demand generation, pipeline, revenue, and market expansion. Build executive relationships, lead business reviews, shape services-led go-to-market initiatives, and collaborate cross-functionally on partner activation and customer adoption. Travel across Asia may be required.

The role involves developing AI-driven solutions for semiconductor engineering, focusing on GenAI systems, data pipelines, and machine learning models while collaborating with cross-functional teams.

Lead global analytics and data science teams supporting semiconductor manufacturing. Drive yield and process optimization through SQL, sensor, and fabrication-tool data; apply statistical modeling and machine learning to reduce defects; support DOE experiments; build automated dashboards; and manage cross-functional delivery portfolios. Mentor technical talent, improve data quality and platform performance, standardize modern data stacks, and partner with engineering and business leaders on prioritization, risks, and dependencies.

Design and implement advanced smart manufacturing solutions in scheduling, mathematical optimization, and discrete event simulation. Build data analytics and applications to provide actionable insights, collaborate globally to deploy solutions across manufacturing sites, and integrate AI/OR hybrid methods to improve production performance and benchmarking.

Analyze semiconductor manufacturing data to identify yield detractors, reduce process variation, and improve device yield. Build data pipelines and automated processes using data from SQL databases, sensors, and fabrication tools. Apply statistical modeling, machine learning, and DOE analysis to solve production issues and support root cause investigations. Create dashboards and reports with visualization tools, collaborate with process engineering teams, and responsibly use AI-enabled tools to improve manufacturing outcomes.

Analyze semiconductor manufacturing, inline, parametric, probe, sensor, and fabrication-tool data to identify yield detractors and reduce defects. Build data pipelines, automate analysis, apply statistical modeling and machine learning, support Design of Experiments, and create dashboards and reports using Dash, Plotly, or Angular. Collaborate with manufacturing, process, equipment, and integration engineers to optimize processes and communicate findings.

Lead data science strategy for AML and financial crime risk controls. Develop AI-powered screening, entity resolution, graph and network intelligence, anomaly detection, transaction monitoring, and proactive discovery of emerging threats. Partner with Product, Engineering, Compliance, and Operations to deliver scalable production controls, influence the roadmap, establish reusable frameworks, and mentor data scientists.

Develop an AI-enabled automation solution for low-yield analysis in semiconductor memory testing. The intern will study test operations, manufacturing systems, test methodologies, data flows, and lot-disposition processes; apply programming, analytics, visualization, and AI tools; validate improvements in efficiency, accuracy, and consistency; and document findings through a final report and presentation.

Summer analysts will build and deploy machine learning, generative AI, and agent-based solutions; integrate complex datasets; develop predictive models; run experiments; analyze trends; and deliver actionable insights. They will also support data governance, risk management, data quality, privacy, and regulatory controls while collaborating with agile, cross-functional teams. The program includes mentorship, training, and potential full-time opportunities after graduation.

Develop and maintain global Data and AI infrastructure supporting data engineering and analytics teams. Lead DevOps strategy, evolve scalable and secure cloud infrastructure, manage operational platforms, build observability and detection capabilities, and establish engineering standards across international teams. The role includes working with Kubernetes, Terraform, GitOps, and data streaming platforms such as Kafka, Flink, or Spark.

The Enterprise Account Executive, Acquisition role focuses on developing a sales strategy within a territory for new customer acquisition, meeting sales targets, and collaborating with Solutions Architects and Professional Services teams.

Lead global analytics engineering initiatives for electronic trading and research. Design, build, and optimize real-time data pipelines, scalable APIs, analytics libraries, and production trading tools. Apply AI to data engineering, analytics, and SDLC automation while ensuring reliability, testing, security, and continuous delivery. Collaborate with trading and research teams, onboard datasets, mentor engineers, manage workstreams, and establish technical standards across distributed teams.

Lead design and deployment of agentic AI for manufacturing planning and operations. Build multi-agent systems combining LLM reasoning and optimization (MIP, heuristics, simulation), integrate agents with data pipelines and enterprise systems, and deliver solutions for capacity planning, production flow optimization, and decision automation. Partner with planning, operations, data engineering, and MLOps teams to translate domain requirements into deployable AI workflows and reusable orchestration frameworks.

Leads smart manufacturing data science initiatives for the F10 organization, serving as the bridge between site leadership, users, and enterprise teams. Responsibilities include prioritizing requirements, driving solution adoption, balancing local support with network best-practice deployment, evaluating capabilities, coordinating cross-functional projects, monitoring deliverables, and managing competing resources and priorities.

Support investment teams by acquiring, cleaning, and analyzing diverse datasets to test investment theses. Learn fundamental investor approaches, identify key data drivers and inflection points, and present research findings. Work with existing and new data to generate insights and decision-support tools for sector-focused investment research.

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.

Generate pipeline and new business across the Philippines and Vietnam through outbound prospecting, account research, prospect qualification, and meeting generation. Build relationships with Account Executives and channel partners, particularly in Vietnam, to identify target accounts and create sales opportunities. Engage IT leaders and executives using phone, email, social selling, events, and other channels while operating in a metrics-driven environment.

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.