Microsoft Senior Applied/Data Scientist 

Taiwan, Taoyuan City 

389841218

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.
• 4+ years of applied science or data science experience

Other Requirements:

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 Cloud background check upon hire/transfer and every two years thereafter.

Preferred Qualifications:

• Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science,
  
  • OR related field
    
  • OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science,
    
  • OR related field AND 6+ years data-science or applied science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
    
  • OR equivalent experience.

• Drive data exploration and analysis by collecting initial datasets, selecting appropriate analytical techniques, and applying foundational statistical methods to extract insights.
• Build and evaluate ML models by running modeling tools on prepared datasets, analyzing performance, and incorporating customer feedback to improve outcomes.
• Contribute to AI development by writing production-quality code for features or models, applying debugging best practices, and staying current with industry trends and methodologies.
• Champion customer-centric solutions by understanding business goals, identifying growth opportunities, and managing expectations throughout the project lifecycle.
• Collaborate cross-functionally with engineering and product teams to define success metrics, improve AI quality at scale, and shape how performance is measured across Copilot technologies.