Microsoft Senior Data Analyst 

Taiwan, Taoyuan City 

428485106

The Scaled Solutions and InsightsData AnalystOperations Service Center stakeholders with a range of data productsand technical solutions to help them gatherdeeper insights and intelligence tocore priorities and strategic planning.

Data Analystwho is willing to work in a dynamic environment. You will need to be adept at managing business change, evolving requirements, adjustments in a strategic direction, and emerging technologies. This is an amazing opportunity to be at the center of building a showcase worthy data capability, the successful candidates should have proven experience inworking with ambiguity,program management,

Required/Minimum Qualifications

• Bachelor's Degree in Statistics, Mathematics, Analytics, Data Science, Engineering, Computer Science, Business, Economics or related field AND 4+years experiencein data analysis and reporting, data science, business intelligence, or business and financial analysis
• • • OR Master's Degree in Mathematics, Analytics, Engineering, Computer Science, Marketing, Business, Economics or related field AND 2+ years’ experience in data analysis and reporting, business intelligence, or business and financial analysis
    • OR equivalent experience.
• 4+years experiencemanaging business change, evolving requirements, adjustments in a strategic direction, OR emerging technologies (ie. Artificial Intelligence).

Preferred Qualifications

• Bachelor's Degree in Statistics, Mathematics, Analytics, Engineering, Computer Science, Marketing, Business, Economics or related field AND 6+ years’ experience in data analysis and reporting, business intelligence, or business and financial analysis
  • • OR Master’s Degree in Mathematics, Analytics, Engineering, Computer Science, Marketing, Business, Economics or related field AND 4+ years experience in data analysis and reporting, business intelligence, or business and financial analysis
    • OR equivalent experience

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:

• Apply in-depth knowledge of the business, evolving data landscape, tools, and technologies to link business topics to relevant data sources and external trends. Anticipate data and business requirements, develop data frames and analytical solutions, andidentifyopportunities to enhance or automate data infrastructure and analyses

• Understand customer needs and perspectives,validaterequirements, and deliver accessible data insights and tools. Build trust byleveraging

• in Data:Appliesexpertisein data sources, formats, and quality toidentifyandleveragedata across multiple sources, understands data requirements, and evaluates the sufficiency of data for addressing relevant and impactful business questions.Determinesandleveragesoptimalmethods and tools for integrating data and proactively works toidentifyand address data integrity, quality, and/or access issues. Recommends opportunities to build new data pipelines or integrations to better meetrequirements, andinitiates collaborative action to sourceadditionaldata. Develops and/or recommends initial/prototype data models and/or tools for others' consumption,leveragesrelevant data and frameworks from other teams, and escalates complex issues with data or data models toappropriate Engineering

• Data Analysis:Appliesexpertisein data, business, and customer needs to evaluate anddetermineideal analytical and statistical techniques to address business and/or research questions. Guides andestablishespartnerships with others to execute complex analyses, resolve analyticalchallenges, interpret results across relevant contexts, and provide actionable recommendations. Critically evaluates the choice of tools, techniques, and assumptions to highlight potential gaps and ensure they areutilized

• Reporting and Sharing Results:

• Experimentation and Innovation:Design and execute formal experiments or prototypes to evaluate the impact of new features or processes. Partner cross-functionally to advise on experimental design and evaluationframeworks, and

• Improvement and Efficiency:Promote methods for efficient analytics and reporting, automate ad-hoc analyses, andparticipatein peer reviews to ensure quality and relevance. Recommend and socializeoptimalmethods for operationalizing, sharing, and scaling insights.Shares critical domainexpertiseto create clarity, ensure readiness to appropriately consume and leverage data and/or insights, and evaluate the viability of automated methods for use in data collection, reporting, and/or analysis.

• Data Model Evaluation:Understandsand evaluates therelationship between analytical model(s) and businessobjectives, highlight gaps, and presentsfindings to senior stakeholders. Establish clear linkage between generated data models and desired businessobjectives.Coaches andmentorslessexperiencedanalysts as

• rchestration and Collaboration:Collaborate with internal stakeholders to ensure quality execution of data sourcing, analysis, and the adoption of best practices. Leverageexpertisetoidentifyareas for innovation and address evolving business needs.

• Maintainexpertisein data privacy and security requirements, ensure compliance with regulations, and enforce standards related to data usage and handling. Guide others to uphold and apply updated data privacy and governance standards.

• mbody our