Microsoft Senior Data Scientist 

Taiwan, Taoyuan City 

849548214

Microsoft is a company where passionate innovators come to collaborate, envision what can be and take their careers to levels they cannot achieve anywhere else. This is a world of more possibilities, more innovation, more openness in a cloud-enabled world.is responsible forthe Microsoft Dynamics 365 suite of products, Power Apps, Power Automate, Dataverse, AI Builder, Microsoft Industry Solution and more. Microsoft is considered one of the leaders in Software as a Service in the world of business applications and this organization is at the heart of how business applications are designed and delivered.

This is an exciting time to join our group and work on something highly strategic to Microsoft. Microsoft Dataverse is the platform to securely store an enormous amount of data in a cost efficient,and easily manageable way. This team builds a suite of microservices to get near real-time insights over your data in Microsoft CES TeamYou will be a part of a team of engineers who thrive on solving complex problems at scale while doing it with impeccable quality.

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

• Bachelor’s degree in Computer Science, Statistics, Electrical/Computer Engineering,Physics, Mathematicsor related field AND 7+ years of experience in AI/ML, predictive analytics, or research- OR Master’s degree AND 7+ years of experience- ORPhDAND 4+ year of experience- OR equivalent experience

• + years of experience withgenerativeAIOR LLM/ML

Other Requirements:

• to meet Microsoft, customer and/or government security screening requirementsarerequiredfor this role.
• Microsoft Cloud Background Check: This position will berequiredto pass the Microsoft Cloud Background Check upon hire/transfer and every two years thereafter.

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

As a Senior AI Applied Scientistfor (insert specific team within BIC), you will play a pivotal role in advancing Microsoft's mission to empower every individual and organization on the planet to achieve more. You will contribute to the development and integration ofAI technologies into Microsoft products and services, ensuring they are inclusive, ethical, and impactful.You will collaborate acrossin machine learning, data science, and AI to solve complex problems. Your work will directly influence product direction and customer experiences.

AI

We are in an era of unprecedented innovation and openness. As Microsoft continues to lead in AI, we are seeking individuals to help tackle some of the most exciting and meaningful challenges in the field. Our vision is to builda truly open architecture platform that enables users to summon tailored AI agents to drive real-world outcomes.

(insert role/ external title)This rolewill combineAI knowledge withapplied sciencedemonstrate a growth mindset. Join us in shaping the future of AI agents.

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

Bringing the State of the Art to Products

• Build collaborative relationships with product and business groups to deliver AI-driven impact
• Research and implementstate-of-the-artusing foundation models, prompt engineering, RAG, graphs, multi-agent architectures, as well as classical machine learning techniques.
• Fine-tune foundation models using domain-specificdatasets. -Evaluate model behavior on relevance, bias, hallucination, and response qualityvia offline evaluations, shadow experiments, online experiments, and ROI analysis.
• Build rapid AI solution prototypes, contribute to production deployment of these solutions, debug production code, supportMLOps/AIOps.Contribute to papers, patents, and conferencepresentations. -Translate research into production-ready solutionsand measure their impact through A/B testing and telemetrythat addresscustomer needs.
• Ability to use data toidentifygaps in AI quality, uncover insights and implementPoCsto show proof of concepts.

Leveraging Researchin real-world problems

• deepexpertisein AI subfields (e.g.,deep learning, Generative AI,NLP,muti-modal models)to translatecutting-edgeresearch into practical, real-world solutions that drive product innovation and business impact.
• Share insights on industry trends and applied technologies with engineering and product teams.
• Formulate strategic plans that integratestate-of-the-artresearch to meet business goals.

Documentation

• Maintain clear documentation of experiments, results, and methodologies.
• Share findings through internal forums, newsletters, and demos to promote innovation and knowledge sharing

,and Security

• Apply a deep understanding of fairness and bias in AI by proactivelyidentifyingand mitigating ethical and security risks—includingXPIA(Cross-Prompt Injection Attack)unfairness, bias, and privacy concerns—to ensureequitableand responsible outcomes.
• Ensure responsible AI practices throughout the development lifecycle, from data collection to deployment and monitoring.
• Contribute to internal ethics and privacy policies andensure responsible AIpracticethroughout AI development cyclefrom data collectionto model development, deployment, and monitoring.

Specialty Responsibilities

• Design, develop, and integrate generative AI solutions usingfoundation models and more.
• Deep understanding ofsmall and large language models architecture, Deep learning, fine tuning techniques, multi-agent architectures, classicalML,andoptimization techniques to adapt out-of-the-box solutions toparticular businessproblems
• Prepare and analyze data for machine learning,identifyingoptimalfeatures and addressing data gaps.
• Develop, train, and evaluate machine learning models and algorithms to solve complex business problems, using modern frameworks andstate-of-the-artmodels, open-source libraries, statistical tools, and rigorous metrics
• Address scalability and performance issues using large-scale computing frameworks.
• Monitor model behavior,,guide product monitoring andalerting,andadapt to changes in data streams.