Microsoft Senior Applied Scientist 

Taiwan, Taoyuan City 

26442156

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.

• 2+ years of industry data science experience
• 4+ years of experience with data science programming tools such as R, SQL, and Excel

Preferred / Additional Qualifications:

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 3+ years related experience (e.g., statistics, predictive analytics, research) OR equivalent experience.

• Experience with machine learning frameworks (e.g., TensorFlow, PyTorch)
• Experience building large-scale, cloud-based solutions
• Strong customer focus, strategic mindset, and ability to drive results
• Self-motivated with a strong bias for action
• Exceptional problem-solving skills—ability to tackle challenges that have never been solved before

• Apply state-of-the-art research and advanced algorithms to develop scalable, data-driven solutions that deliver measurable product impact.
• Collaborate with product, engineering, and research teams to transfer technology and integrate innovative approaches into production systems.
• Design and optimize machine learning models and data pipelines for large-scale applications, ensuring performance, scalability, and ethical standards.
• Mentor and guide less experienced team members, fostering technical growth and sharing best practices across projects.
• Stay current with industry trends and emerging technologies; publish research and share insights to advance innovation and business impact.
• Incorporate fairness, bias detection, and privacy considerations into research and product development processes.
• Drive improvements in data quality and leverage advanced analytics to identify opportunities for product enhancement.