Microsoft Senior Applied Scientist 

Taiwan, Taoyuan City 

889803085

. In this role, you will drive

Required Qualifications:

• Bachelor's Degree in Statistics, Econometrics, 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 Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research)
  • OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research)
  • OR equivalent experience.
• Experience: 4+ years of industry experience in applied machine learning or data science roles.
• Technical Skills:Proficiencyin Python and ML libraries (e.g.,PyTorch, TensorFlow). Experience with NLP, generative models, or content understanding is highly desirable.
• Communication: Strong written and verbal communication skills. Ability to explain complex technical concepts to non-technical stakeholders.
• Problem Solving:Demonstratedability to tackle open-ended problems and deliver practical, scalable solutions.

Preferred Qualifications:

• Master’s degree with 6+ years of experience or Ph.D. with 3+ years of experience in a relevant field.
• Experience contributing to research publications, patents, or open-source projects.
• Hands-on experience deploying ML models in production environments.
• Familiarity with the full product lifecycle, from ideation to deployment and iteration.

• Applied Research & Development: Design and implement machine learning models and algorithms that improve search, summarization, and content understanding in Office applications. Stay current with advancements in NLP and generative AI to inform product innovation.
• Model Development & Deployment: Build andoptimizeML/DL models using frameworks likePyTorchor TensorFlow. Contribute to the deployment of models in production environments, ensuring scalability and performance.
• Cross-Functional Collaboration: Work closely with engineering, product, and research teams to define goals, align on priorities, and deliver impactful features. Translate business needs into technical solutions.
• Experimentation & Evaluation: Conduct experiments to evaluate model performance,analyzeresults, and iterate on solutions. Use data-driven insights to improve precision, recall, and user satisfaction.
• Innovation & Impact: Explore new signals, data sources, andmodelingtechniques to enhance intelligent systems. Contribute to the evolution of the Copilot ecosystem and agentic experiences in Office.