Principal Data Science Manager

The SharePoint Data Science team champions a data-driven culture, enabling informed decisions across the organization. Collaborating with engineering, marketing, finance, and business leaders, we uncover opportunities to enhance customer experiences and drive product growth. Our team analyzes data trends, delivers performance insights, builds predictive models, recommends actions, and conducts experiments to validate impact.  As we continue to innovate, we are increasingly incorporating state-of-the-art 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.

We seek an experienced Principal Data Science Manager to lead a team focused on unlocking new value for Microsoft customers by analyzing product consumption across SharePoint. Use your expertise in data science and product offerings to help deliver exceptional experiences for our customers and partners.

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

Responsibilities

• Set the vision, drive prioritization, and guide technical approaches for leveraging data across SharePoint and Microsoft 365 products to identify and pursue the right business opportunities.
• Translate complex data insights into actionable product strategies by blending analytical rigor with strategic clarity.
• Hire and develop 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 understand objectives and identify opportunities. Collaborate closely with other Microsoft Data Science and Data Engineering teams to deliver data-informed solutions to address the business's most essential needs.
• 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/B product experimentation through strategy, experiment design, and metrics definitions.
• Serve as a leader within the organization by creating clarity, inspiring others, and delivering high quality.

Qualifications

Required Qualifications:

• Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ 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 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.
• 3+ years people-management experience.
• 3+ years of experience recruiting and managing data scientists, program/product managers, business/data analysts, or related roles from industry and/or academia.
  
• Demonstrated experience as an organizational leader.
• Functional knowledge of cloud computing and online services business models, including business, technical, financial, and operational measurements.

Other Requirements: 

Candidates must be able to meet Microsoft, customer and/or government security screening requirements that are required for this role. These requirements include, but are not limited to the following specialized security screenings:  

• Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.

Preferred 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.
• 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 experiences.
• 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. Examples include causal inference, resampling techniques, mixed effects models, significance tests, etc.
  
• Knowledgeable about data storage patterns and tradeoffs.
  
• Fluent in tools for navigating and analyzing data (SQL, Azure Data Explorer, R, Python, Databricks, etc.).

Data Science M5 - The typical base pay range for this role across the U.S. is USD $139,900 - $274,800 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $188,000 - $304,200 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: https://careers.microsoft.com/us/en/us-corporate-pay

Microsoft will accept applications for the role until June 21, 2025.

 

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances.  We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request via the Accommodation request form.

 

Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.