Microsoft Principal Data Science Manager 

United States, Washington 

49971545

recommend actions to be taken, and run experiments to prove that desired outcomes are being achieved.

AI technologies, including Language Learning Models (LLMs), to transform our data science processes. These advancements are not only improving our analytical capabilities but also automating complex tasks and refining our approach to big data, making our insights more actionable and precise.

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product and servicesorganizations on how they. We use data to organize our backlogs. We empower our industry

Required Qualifications:

• Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ year(s) 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 7+ 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 10+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
  • OR equivalent experience.
• 5+ years of progressive experience delivering actionable business insights and helping to shape business and product strategy.
• 3+ years people-management experience.

Preferred Qualifications:

• Demonstrated experience as an organizational leader.Three plusyears of experience recruiting and managing data scientists, program/product managers, business/data analysts,or related roles from industry and/or academia.
• Functional knowledge of cloud computing and online services business models, including business, technical, financial, and operational measurements.
• Proven business acumen to understand which projects best support overall business strategy and which types of data insights apply to strategic goals.
• Excellent quantitative, data modeling, and statistical skills.Examplesincludecausal inference, resampling techniques, mixed effects models, significance tests, etc.
• Knowledgeableabout datastorage patterns and tradeoffs.
• Fluent in tools for navigating and analyzing data (SQL, Azure Data Explorer, R, Python, Databricks, etc.).
• Experience with machine learning algorithms for forecasting, clustering, classification, recommendation systems, NLP, etc.
• Advanced degree inaquantitative field.

Interpersonal Skills:

• Excellent written and oral communication skills, particularly the ability to synthesize complex problems/scenarios into easy-to-understand concepts.
• Able to deliver compelling presentations to audiences at all levels of the organization.
• Creative, innovative, and organized thinker with high attention to detail.
• Self-driven to continuously learn and bring a growth mindset to problem-solving.
• Effective time management in complex, ambiguous, deadline-driven environments.
• Proven ability to create a healthy team culture of diversity, inclusion, belonging, and collaboration.
• Demonstrated interest and empathy for understanding customer scenarios and

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 June 15, 2024.

. You willbe responsible forthe backlog and strategyengineers and working with abroad cross-an inclusive culture and growth mindset. You will need to partner effectively with teams across Microsoft to design holistic solutions. This will require technical depth to ensure we maketradeoffs among multiple technology options.

• Set the vision, drive prioritization, and guide technical approaches forleveragingdataacross Microsoft 365 products toidentifyand pursue the right business opportunities.
• Hire and develop top talent - build and cultivate a highly functioning team of data scientists grounded in the objective truth of the measured customer experience.
• Utilize LLMs and other AI technologies to revolutionize data science practices within the team, enhancing the speed, accuracy, and scalability of data analysis and insight generation.
• Develop and manage relationships with product and business leaders across the organization to understandobjectivesandidentifyopportunities. Collaborate closely withother Microsoft Data Scienceand Data Engineering teams to deliver data-informedsolutions to address thebusiness's most essential needs.
• Lead the team in generating data insights that willimpactrevenue growth. Aid the broader team in understanding impacts to revenue streams.
• Create andmaintainadata science and analytics roadmap. Run sprint/quarter/semester planning and foster cross-team collaboration to deliver complex projects.
• Establish success measures that set a high bar of achievement for our organization and drive accountability through our team and partners.
• Contribute to scaled A/Bproductexperimentationthroughstrategy,experiment design, and metricsdefinitions.
• Serve as a leader within the organization by creating clarity, inspiring others, and delivering high quality.