Microsoft Senior Data Scientist 

Taiwan, Taoyuan City 

765650628

Required/Minimum Qualifications

• Minimum of8years(for those withBachelor’s Degree/Master’s Degree) or5years(for those with a Doctorate)of experience as a data scientist implementing data science solutions, with experience in implementing projects in one or more areas amongst: Computer Vision, LLMs, Audio/Voice data processing, and Reinforcement Learning.
• Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, Engineering or related field AND data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
  • ORMaster's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science,Engineeringor related field data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) or consulting experience.
  • OR Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science,Engineeringor related field
• OR equivalent experience.

• Business level Japanese and English language skills.

the following key knowledge,and experience:

• Hands-on software engineering experience (e.g.Python, C++)

• Proven skills and experience in a data science role

• Familiarity with building and deploying largescale AI solutions into production within a cloud environment. Has experience in working withMLOps,LLMOpsand frameworks likeLangChain, Semantic Kernel and Prompt Flow.

• , directly and independently,inensuring that the proposed solution addresses the business needs – through all stagesfrom solutioning todeployment into production.

Data Preparation and Understanding:

Leads data acquisition and understanding efforts for engineering projects using various tools and techniques that support the data science lifecycle.

Modeling and Statistical Analysis:

Develops and applies ML frameworks and best practices for scalable and ethical solutions.

Oversees review of data analysis and modelling techniques. Ensures selected modelling techniques areand align with desired project outcomes.steps (e.g., deployment, further iterations, new projects).

leading edgeconcepts and approaches to the

Coding and Debugging

Writes efficient, readable, extensible code from scratch that spans multiple features/solutions. Develops technicalin proper modeling, coding, and/or debugging techniques such as, isolating, and resolving errors and/or defects. Understands the causes of common defects and uses best practices in preventing them from occurring.