Data Scientist jobs at Microsoft in Taiwan, Taoyuan City

and multi-disciplinary group of scientists,

Principal Data & Applied Scienwork ongroundbreaking andhigh-impact projects at the intersection of AI and software engineering. In this role, you will drive the development and application of advanced data science techniques—especially those involving LLMs—to real-world developer workflows.. You will have the opportunity to design and lead experiments, build and evaluatemodels (including RAG pipelinesand evaluation frameworks), andinsights into scalable product features. Most importantly,play a key role in bridging

Required/Minimum Qualifications:

• degree in Computer Science, Engineering, Mathematics, Statistics

• +yearsexperiencewith strongproficiencyinPython, machine learning frameworks,and experience developing and deploying generative AI or machine learning models into production. (Experience withadditionalprogramming languages is a plus but notrequired

Preferred Qualifications

• or PhD degree in Computer Science, Statistics, or related fields (undergraduates with significantappropriate experiencewill be considered).

• Strong professional experience in statistics, machine learning, including deep learning, NLP, econometrics.

• Experience in building cloud-scale systems and experience working with open-source stacks for data processing and data science is desirable.

• Experience with LLMs in natural language, AI for code or related fields

• Excellent communication skills, ability to present andwritereports, strongteamworkand collaboration skills.

• Experience in productizing AI and collaborating with multidisciplinary teams.

• researchand productization ofstate-of-the-art in AI for Software Engineering

• Build and manage large-scale AI experiments and models.

• Drive experimentation through A/B testing and offline validation to evaluate model performance.

• and geographieswith product teamsinMicrosoft and Github

• Stay up to date with the research literature and product advances in AI for software engineering

• Collaborate with world renowned experts in programming tools and developer tools to integrate AI across software development stack for Copilot

• Lead others by exemplifying growth mindset, inclusiveness, teamwork, and customer obsession

The Security Models Training team builds and operates the large-scale AI training and adaptation engines that power Microsoft Security products, turning cutting-edge research into dependable, production-ready capabilities. As a, you will lead end-to-end model development for security scenarios, including privacy-aware data curation, continual pretraining, task-focused fine-tuning, reinforcement learning, and rigorous evaluation. You will drive training efficiency on distributed GPU systems, deepen model reasoning and tool-use skills, and embed responsible AI and compliance into every stage of the workflow. The role is hands-on and impact-focused, partnering closely with engineering and product to translate innovations into shipped experiences, designing objective benchmarks and quality gates, and mentoring scientists and engineers to scale results across globally distributed teams. You will combine strong coding and experimentation with a systems mindset to accelerate iteration cycles, improve throughput and reliability, and help shape the next generation of secure, trustworthy AI for our customers.

Required Qualifications:

• Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 8+ years related experience (e.g., statistics, predictive analytics, research)
  • OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research)
  • OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 5+ years related experience (e.g., statistics, predictive analytics, research)
  • OR equivalent experience.
• 3+ years experience presenting at conferences or other events in the outside research/industry community as an invited speaker.
• Proven track record training and shipping large language models or multimodal models for production scenarios, including continual pretraining and task specific adaptation.
• Proficiency in Python and PyTorch, with hands-on experience building and debugging large-scale training jobs.

Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include, but are not limited to the following specialized security screenings:

Microsoft Cloud Background Check:
- This position will be required to pass the Microsoft background and Microsoft Cloud background check upon hire/transfer and every two years thereafter.

Preferred Qualifications:

• Security domain experience in one or more areas: security operations, threat intelligence, malware analysis, vulnerability and posture management, anomaly detection, phishing and fraud detection, or cloud identity and access.
• Experience with distributed training and scaling techniques, for example DeepSpeed, FSDP, ZeRO, model and pipeline parallelism, mixed precision, and profiling.
• Experience with privacy preserving ML including differential privacy concepts, privacy risk assessment, and utility measurement on privatized data.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:Microsoft will accept applications for the role until October 21, 2025.

• Lead the full modeling lifecycle for security scenarios, from data ingestion and curation to training, evaluation, deployment, and monitoring.
• Architect and optimize large-scale distributed training on GPU clusters, improving throughput, reliability, and cost efficiency.
• Design and implement privacy-preserving data workflows, including anonymization, templating, synthetic augmentation, and quantitative utility measurement.
• Develop and maintain fine-tuning and adaptation recipes for transformer models, including parameter-efficient methods and reinforcement learning from human or synthetic feedback.
• Establish objective benchmarks, metrics, and automated gates for accuracy, robustness, safety, and performance, enabling repeatable model shipping.
• Collaborate with engineering and product teams to productionize models, harden pipelines, and meet service-level objectives for latency, throughput, and availability.
• Mentor applied scientists and engineers, promote strong documentation and experiment hygiene, and foster a culture of rapid iteration grounded in responsible AI principles.
• Contribute to thought leadership by staying current with the latest AI advances and translating promising techniques into practical, measurable impact.

? The Business and Industry Solutions (BIS) team is looking for a Senior Applied Scientist to drive innovation at the intersection of AI, experimentation, and enterprise systems. In this role, you will design and evaluate autonomous agents that deliver measurable improvements in accuracy, latency, and cost-efficiency.lead rapid experimentation cycles, develop robust evaluation frameworks, and apply advanced techniques like reinforcement learning to enable multi-step reasoning and decision-making.collaborate across engineering, product, and partner teams to ensure agents are performant, secure, reliable, and extensible—empowering customers and partners to build on our platform. This is your opportunity to influence the next generation of AI-native business applications and deliver real-world impact at scale.

in natural language processing (NLP), witha strong foundationin large language model (LLM) development, evaluation, and fine-tuning. They should have hands-on experience in applying advanced fine-tuning techniques—including instruction tuning, reinforcement learning from human feedback (RLHF), and tool-augmented generation—to build agents capable of multi-step reasoning and decision-making. Familiarity with prompt/context engineering, context-aware orchestration, and integrating LLMs with external tools and APIs is essential. The candidate should be comfortable working in a fast-paced, experimentation-driven environment,both offline and online evaluation methods to iterate rapidly andagent behavior. A deep understanding of the challenges and opportunities in building AI-native enterprise applications will be key to success in this role.

Qualifications

• Bachelor's Degree in Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics, predictive analytics, research)

• OR Master's Degree in Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research)

• OR Doctorate in Computer Science, Electrical or Computer Engineering, or related field AND 1+ years related experience (e.g., statistics, predictive analytics, research)

• OR equivalent experience.
• 1+ years of experience withgenerativeAIOR LLM/ML

Preferred Qualifications:

• Experience withMLOpsWorkflows, including CI/CD, monitoring, and retraining pipelines

• Familiarity with modernLLMOpsframeworks (e.g.,LangChain,PromptFlow

• 3+ years of experience publishing in peer-reviewed venues or filing patents.

• Experience presenting at conferences or industry events

• 3+ years of experience conducting research in academic or industry settings
• 1+ year of experience developing and deploying live production systems

• 1+ years of experience working with Generative AI models and ML stacks
• Experience across the product lifecycle from ideation to shipping

and/or government security screening requirementsfor this role. These requirements include but are not limited to the following specialized security screenings:

• requiredto pass the Microsoft Cloud Background Check upon hire/transfer and every two years thereafter.

• by executing high‑leverage data science and analytics initiatives within a product area or feature team, ensuring measurable improvements to user and business outcomes.

• Lead the design and implementationof advanced model fine‑tuning pipelines, including Reinforcement Learning from Human Feedback (RLHF), to align AI system behavior with user intent and improve performance in real‑world scenarios.

• Own complex, end‑to‑end projectsthat combine technical depth with cross‑functional collaboration, influencing feature direction and prioritization rather than broad organizational investment decisions.

• Foster alignment and trustacross partner teams through clear, actionable communication and collaborative problem‑solving.

• Develop and maintainrobust measurement systems, experimentation frameworks, and causal inference methodologies tailored to dynamic AI systems and enterprise‑scale environments.

• Mentor and supportpeers by sharing best practices, reviewing designs, and contributing to a collaborative, high‑performance team culture.

• Leverage AI tostreamline workflows and enhance team productivity through intelligent automation and innovation.

At , we believe machine learning and artificial intelligence has the potential to transform scientific modelling and discovery crucial for solving the most pressing problems facing society including sustainable materials and discovery of new drugs.

Required:

• PhD or equivalent experience in Computer Science, Machine Learning, Applied Mathematics, Computational Biology, or related field.
• Strong software engineering in Python (packaging, testing, CI), with systems thinking for data‑intensive ML.
• Deep learning experience (PyTorch/JAX/TensorFlow) and solid foundations in linear algebra, probability, and statistics.
• Proven experience designing robust data pipelines for large‑scale ML (HPC or cloud).
• Ability to reason about learning signal and to assess information content of real‑world scientific datasets.
• Excellent collaboration and communication in interdisciplinary teams.

Preferred:

• Hands‑on cryo‑EM experience (e.g., map reconstruction, refinement, or pipeline tooling).
• CUDA or C++ for performance‑critical components; experience with mixed precision and memory‑efficient training.
• Experience integrating experimental data into ML models (e.g., constraints/priors from cryo‑EM, binding assays, spectroscopy).
• Familiarity with MD data, structure prediction systems, or protein design work-flows.
• Experience with cost‑optimization for data collection and cloud utilization; clear track record of building reliable, maintainable research software at scale.
• Experience with structural biology or molecular biology data/techniques (e.g., cryo‑EM, binding assays, spectroscopy, expression, sequencing)

• Data integration for structure & dynamics: Build ingestion/curation pipelines for structural/biophysical data (mmCIF/PDB, EM maps/particles, binding/biophysics, spectroscopy); implement map/volume preprocessing (e.g., resolution filtering, normalization) and alignment to model inputs/outputs.
• Cryo‑EM expertise: Operationalize end‑to‑end flows from raw image stacks/particles to 3D maps and model‑ready tensors; interoperate with community formats (e.g., EMDB/EMPIAR, mmCIF) and link to sequences/annotations.
• Signal & information content: Design dataset diagnostics (e.g., mutual‑information‑like measures, effective sample size, SNR proxies) to quantify what data teach the model; build active‑learning loops that maximize learning per euro of data collection time.
• Model‑aware data services: Implement scalable, versioned data services and feature stores that feed training/evaluation; design loaders/augmentations optimized for throughput and correctness (GPU‑aware).
• Training‑at‑scale engineering: Own distributed data pipelines and orchestration for large runs on Azure; profile and tune I/O, storage tiers, data locality, and caching; monitor cost, utilization, and failure modes.
• Quality, governance, and reproducibility: Codify schemas/ontologies, metadata contracts, unit/integration tests, and lineage; automate validation and data drift detection; maintain documentation and examples.
• Partner across disciplines: Work closely with ML researchers, structural biologists, and drug designers; translate experimental constraints into robust computational workflows; communicate clearly and proactively.

As part of the Cloud + AI Data team, you’ll leverage existing Repeatable IP and execution engines with accountability to drive delivery excellence, accelerate adoption, and ensure a successful deployment for the customer for services such as Microsoft Fabric, Azure Databricks, OpenAI, Cosmos DB, Purview. You’ll collaborate with different teams across Microsoft, share best practices, and stay current with evolving trends to help customers unlock the full value of their data and AI investments.

Your Role and Impact:

• Strategic Guidance: Engage with customers & partners to understand their goals and challenges, then provide strategic solutions that maximize the value of their Microsoft technology investments.
• Technical Leadership: Lead in-depth technical discussions, offering insights and recommendations to overcome complex challenges in data and AI initiatives both On-premises (SQL Server) as well as in Azure.
• Empowering Customers & Partners: Support customers & Partners in achieving successful outcomes by developing tailored solutions that drive their digital transformation and innovation.
• Continuous Growth: Leverage this opportunity to advance your career while enhancing your knowledge and skills in cutting-edge cloud technologies.

Bachelor’s degree in computer science, Information Technology, Engineering, Business, or related field AND 12+ years’ experience in cloud/infrastructure technologies, information technology (IT) consulting/support, systems administration, network operations, software development/support, technology solutions, practice development, architecture, and/or consulting

OR Master's Degree in Computer Science, Information Technology, Engineering, Business, or related field AND 8+ years experience in cloud/infrastructure technologies, technology solutions, practice development, architecture, and/or consulting

OR equivalent experience

6+ years experience working in a customer-facing role (e.g., internal and/or external).

6+ years experience working on technical projects

• 5+ years of experience with SQL Server, SQL Server on Azure VMs, Azure SQL DB, and/or Azure SQL Managed Instance, Data Warehouses, Power BI.

• Experience in SQL Server at scale, on-premises to Azure migrations, complex SQL Server troubleshooting, performance tuning and optimization, scaling OLTP and OLAP workloads, and securing SQL Server on-premises or in Azure.

Technical Certifications in Cloud (e.g., Azure, Azure Data Platform, Power BI, Amazon Web Services, Google, security certifications).

Technical experience and knowledge in Enterprise-scale technical experience with On-premises, cloud and hybrid infrastructures, architecture designs, migrations, and technology management.

Other Key Requirements

• Chinese (Mandarin) language skill at highest proficiency level is a Must have skill. It will be great advantage if applicant knows Cantonese as well as Mandarin.
• Advanced written, spoken English level with direct customer facing experience.
• Note: Microsoft is unable to sponsor a work visa for this role due to the nature of the role’s job duties.

• Enterprise-scale technical experience with cloud and hybrid infrastructures, architecture designs, database migrations, and technology management.
• Breadth of technical experience and knowledge, with depth / Subject Matter Expertise in two or more of the following Data Platform and Analytics Cloud solutions :
• SQL Server/Database and OSS database (PostgreSQL, MySQL etc)
• Azure Databases (Azure SQL, Azure Postgres SQL, Azure MySQL, Cosmos DB)
• Power BI
• Microsoft Fabric (Fabric DW, Real-Time Intelligence, OneLake, Data Integration, Data Engineering, Copilot, Data Science)
• Azure Databricks
• Microsoft Purview
• Azure AI Foundry
• Hyperscale
• Azure Data Factory
• Azure Machine Learning
• Azure Open AI
• Cognitive services
• NoSQL Databases including OSS (Cassandra, Mongo, and HBase etc)
• Big Data platform such as Synapse, Snowflake, Big Query, Redshift, Spark
• Advanced Analytics including Azure Synapse, Databricks, and visualization tools such as PowerBI, Tableau.
• Data Science and Data Engineering including machine learning framework such as PyTorch and scikit-learn.
• Streaming, IoT, Real-time analytics
• Expertise in data estate workloads like HDInsight, Hadoop, Cloudera, Spark, Python
• The technical aptitude and experience to learn new technologies and understand relevant cloud trend
• Competitive Landscape: Knowledge of cloud development platforms
• Understanding of partner ecosystems and the ability to leverage partner solutions to solve customer needs
• Expertise in AI like LLM Preferred

• You will develop relationships with key customer IT and business decision makers, to understand their data estate, priorities, and success measures, and design secure, scalable Data & AI solutions that deliver measurable business value.

• You will understand customers’ overall data estate Business and IT priorities and success measures to design Data & Analytics solutions that drive business value and drive positive Customer Satisfaction & become a trusted advisor.

• You will ensure that solution exhibits high levels of performance, security, scalability, maintainability, repeatability, appropriate reusability, and reliability upon deployment and provide feedback and insights from customers/partners.

• You will develop opportunities to drive Customer Success business results & help Customers get value from their Microsoft investments and identify resolutions to Customer blockers by leveraging subject matter expertise. Deliver according to MS best practices & using repeatable Intellectual Property (IP).

• You will apply technical knowledge to architect and design solutions that meet business and IT needs, create Data & Analytics roadmaps, drive Proof of Concepts (POC) and Minimal Viable Product (MVP), and ensure long term technical viability of new deployments, infusing key AI technologies where appropriate.

• You will maintain technical skills and knowledge, keep up to date with market trends and competitive insights; collaborate and share with the AI technical community while educating customers on Azure platform.

• You will accelerate customer outcomes - Share expertise, contribute to IP creation & re-use to accelerate customer outcomes and obtain relevant accreditations and certifications. Proactively identify gaps through delivery and communicating those gaps to others (e.g., Leadership, managed intellectual property [MIP], Design, and Governance). Applies subject matter expertise to develop new IP that fills identified gaps

• Drive Azure consumption through accurate and complete Azure Consumption Plans and support Unified/Factory delivery models.

• Lead technical workshops, build MVPs, and guide customers through production deployments.
• Collaborate with internal teams to remove blockers and share customer feedback.
• Evangelize Azure technologies within customer, partner, and community ecosystems.

• Own the end-to-end technical delivery results, ensuring completeness and accuracy of consumption and customer success plans in collaboration with the Customer Success Account Managers.

• Provide delivery oversight and escalation support for key consumption engagements across Data & Analytics workloads.

• Drive technical excellence by leading the health, resiliency, security, and optimization of mission-critical data workloads, ensuring readiness for production-scale AI use cases.

• You will identify resolutions to issues blocking go-live of migration and modernization projects by leveraging Azure Infrastructure technical subject matter expertise and lead technical conversations with customers to drive value from their Microsoft investments and deliver all work according to MS best practices and policies.

• You will demonstrate a self-learner mindset through continuous alignment of individual skilling to team/area demands and Customer Success goals as you accelerate customer outcomes and engage in relevant communities to share expertise, contribute to IP creation, prioritize IP reuse and learn from others to help accelerate your customers transformation journey.

• Be accredited and certified to deliver with advanced and expert-level proficiency in priority workloads including Microsoft Fabric, Azure Databricks, Microsoft Purview, Azure SQL, PostgreSQL, MySQL, and Cosmos DB.

Technical leadership

• Design the solution using your Data Platform technical knowledge, architectural approach, consultancy skills and our methodology to win a customer’s technical decision and meet the customer’s needs; drive proof of concepts (POCs)/production deployments to create momentum for MVPs, infusing key AI technologies where appropriate and being technically proficient to do POC with hands-on-skills.

• Data Platform technologies, including SQL Server, Azure SQL Database, and Azure Cosmos DB, as well as Analytics, Data Warehousing, and Data Engineering scenarios. Focus on Intelligent Data and Analytics Platforms such as Synapse, Lakehouse architecture, Fabric, Azure Databricks, and Power BI. Stay informed on market trends and competitive insights and actively collaborate and share knowledge within the Data & AI technical community.

• Experience in Azure architecture design, Azure IaaS, Azure SQL Database, Azure SQL Managed Instance, High Availability, service resilience and distributed systems.

• Experience as a Database Administrator, data platform design, SQL Server at scale, on-premises to Azure migrations, complex SQL Server troubleshooting, performance tuning and optimization, scaling OLTP and OLAP workloads, and securing SQL Server on-premises or in Azure

• Experience with High Availability/Disaster Recovery solutions such as Failover Clustering, Database Mirroring, Always-On Availability Groups, and Replication

• Use trace analysis, debug skills, source code, and other proprietary tools, to analyse problems and develop solutions to meet customer needs; this may involve writing code

• Consultative experience along with presentation skills with a high degree of comfort with both large and small audiences

• Learns to identify and communicate areas in intellectual property (IP) that need refreshing or have gaps. Contributes to IP development with guidance/supervision.

• Demonstrates strong industry knowledge and increases recognition for Microsoft solutions by contributing to and sometimes leading presentations and engagements with external and internal audiences (e.g., Tech Connect, Build, Ignite)

Required Qualifications:

• Proven years years technical pre-sales or technical consulting experience
• Expert in Azure Databases (SQL DB, Cosmos DB, PostgreSQL) from migration & modernize and creating new AI apps OR Equivalent experience.
• Expert in Azure Analytics (Fabric, Azure Databricks, Purview) OR competitors (BigQuery, Redshift, Snowflake) in data warehouse, data lake, big data, analytics, real-time intelligent, and reporting using integrated Data Security & Governance.
• Proven ability to lead technical engagements (e.g., hackathons, PoCs, MVPs) that drive production-scale outcomes.

Preferred Qualifications:

• Degree in Computer Science, Information
• Several years technical pre-sales, technical consulting, or technology delivery, or related experience
• Proven years experience with cloud and hybrid, or on premises infrastructure, architecture designs, migrations, industry standards, and/or technology management
• Proficient on data warehouse & big data migration including on-prem appliance (Teradata, Netezza, Oracle), Hadoop (Cloudera, Hortonworks) and Azure Synapse Gen2.
• Proficiency in Danish is preferred.

• Drive technical sales with decision makers using demos and PoCs to influence solution design and enable production deployments.
• Lead hands-on engagements—hackathons and architecture workshops—to accelerate adoption of Microsoft’s cloud platforms.
• Build trusted relationships with platform leads, co-designing secure, scalable architectures and solutions
• Resolve technical blockers and objections, collaborating with engineering to share insights and improve products.
• Maintain deep expertise in Analytics Portfolio: Microsoft Fabric (OneLake, DW, real-time intelligence, BI, Copilot), Azure Databricks, Purview Data Governance and Azure Databases: SQL DB, Cosmos DB, PostgreSQL.
• Maintain and grow expertise in on-prem EDW (Teradata, Netezza, Exadata), Hadoop & BI solutions.
• Represent Microsoft through thought leadership in cloud Database & Analytics communities and customer forums