Microsoft Senior Director Marketing Data Science 

Taiwan, Taoyuan City 

405324776

Required/Minimum Qualifications

• Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 8+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 10+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 12+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR equivalent experience.
• 5+ years people-management experience.
• Experiencehandling large data sets to reveal patterns, trends, and associations, from behavioral and interaction data to uncover important factors that can influence outcomes.
• Experience with one or more AI/ML algorithms and frameworks and their application to solve various business problems. Examples include causal inference, resampling techniques, mixed effects models, clustering, classification, significance tests, time-series modeling/forecasting, etc.

Additional or Preferred Qualifications

• Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 10+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 12+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 15+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR equivalent experience.
• 7+ years people-management experience.

• Experience with Large Language Models (LLMs), prompt engineering, and Azure AI Application Programming Interfaces (APIs)
• Experience with Machine Learning Operations (MLOps) practices: containerization, infrastructure-as-code, monitoring
• Experience with multi-agent frameworks like AutoGen, Semantic Kernel, and Langchain
• Experience in debugging, security, and data protection principles

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:Microsoft will accept applications for the role until October 25, 2025.

• Demonstrate a commitment to Microsoft’s data security and privacy standards as the top priority in all analytics, reports, and solutions we develop.
• Lead large, complex projects to deliver accurate, accessible, secure and repeatable data products aligned to business and organizational needs and priorities that enhance our ability to inform marketing efforts, increase effectiveness of our approaches and deliver measurable outcomes.
• Demonstrate leadership in business and data landscape, visualizations, experimentation, and analysis to effectively communicate and support data driven decision making.
• Foster a team that embraces and lives Microsoft’s Culture and Values.
• Design and implement repeatable and scalable statistical and Machine Learning (ML) based frameworks to identify changes in behavior, business performance and other outcomes to help us make predictions and recommendations, set forecasts, identify anomalous activities, and understand outcome trajectory.
• Partner with Data Services on technical requirements to ensure adherence to security and compliance guidelines and enable data availability, data quality and integrity for data science, analytics and wider business self-service usage.
• Establish processes for the development of experimental methodologies, statistics, optimization, and probability theory for general purpose software and statistical packages. Leverages results from modeling and analyses to influence business and/or product strategy and leadership across teams.
• Deliver success through empowerment and accountability by modeling, coaching, and caring. Model: Live our culture. Embody our values. Practice our leadership principles. Coach: Define team objectives and outcomes. Enable success across boundaries. Help the team adapt and learn. Care: Attract and retain great people. Know each individual’s capabilities and aspirations. Invest in the growth of others.
• Embody our and