Principal Data Scientist

The Customer Solutions Area (CSA) organization sits at the center of our Commercial business, responsible for defining, landing and operating our Commercial go-to-market (GTM), connecting sales, marketing and engineering with field, customers and partners to bring ideas and products from incubation to scale across all customers we serve, while delivering on Microsoft’s mission.  
 
Within the CSA organization, the Business Insights team partners across our Commercial Solution Areas, working with GTM strategy, programs, enablement, global sales, engineering and field teams to generate business insights that influence the shape and direction of our business, sales strategy to accelerate the growth of our business. Our charter spans the breadth of the solution areas, where we design and deliver standardized views of business performance, pipeline health, build predictive analytics and propensity models, analyze productivity trends and competitive threats to surface actionable business insights.   
 
As Principal Data Scientist, you will play a critical cross-team role, leveraging your deep technical depth and experience with data engineering, statistics, data analysis, data science and visualization to design, optimize and manage the core data platform that enables our insights delivery. As an experienced data engineer, you will question prior assumptions and proactively seek innovative solutions to meet our seller’s needs, sales leaders’ needs and executive needs – charting the story of the business in a connected way that helps drive the right behaviors from sellers, partners and leaders.  

The ideal candidate must be dynamic, passionate, self-motivated, confident in working with and be able to gain the trust of the stakeholders across the organization and drive results through influencing the work of others.

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.

In alignment with our Microsoft values, we are committed to cultivating an inclusive work environment for all employees to positively impact our culture every day.

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.
• Experience in managing AND using Azure services such as Power BI, Fabric, Azure Data Explorer, Azure SQL, or third parties equivalent (i.e. Snowflake on Azure) within the last 12 months.

Data Science IC5 - 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 September 15, 2025.

• Business understanding and impact. Leverages understanding of data science and business to examine a project and consider factors that can influence final outcomes. Documents key business objectives. Effectively communicates business goals in analytical and technical terms. Consistently shares insights with stakeholders.
• Data Engineering. Understands where to acquire data necessary for successful completion of the project plan. Utilizes querying, visualization, and reporting techniques to describe acquired data, including format, quantity, identities, and other surface properties. Collaborates with others to perform data-science experiments using established methodologies, statistics, optimization, and probability theory for general purpose software and statistical packages. Serves as an effective partner in data preparation efforts to Solution Architects and other business stakeholders (Commercial Solution Areas). Adheres to Microsoft's privacy and security policies related to collecting and preparing data. Identifies data integrity problems.
• Business Insights Warehouse. Establishes and maintains a scalable data warehouse leveraging Microsoft Fabric and Azure data platforms (Azure Data Explorer, Azure Data Factory, and Databricks) to support data science teams on building data-driven insights, forecasting, propensity modeling, and customer targeting efficiently.
• Infrastructure. Maintain team’s Azure subscription, managing resources to optimize performance inside the available budget. Ensure the data warehouse and involve Azure resources meet security and privacy compliance and AI readiness requirements. Evolve data platform to meet new requirements, including leveraging new Microsoft technologies, with the objective of improving productivity and showcasing the latest Microsoft innovations.
• Business and Research Knowledge/Opportunity Identification. Learns and understands the current state of the Commercials Solution Areas business, including knowledge of tools, techniques, strategies, and processes that can be utilized to improve process efficiency and performance. Maintains knowledge of current trends within the discipline.
• Business Insights AI Innovation. Leveraging the latest technology, drive an innovation agenda, integrating AI to transform insights delivery.
• Other:
  • Be a hands-on technical lead who can own, drive, and develop data platform from conception to release.
  • Be curious and willing to continuously learn about the business; partner with stakeholders to define the critical insights required to make informed business decisions and sales precision.
  • Continuously evolve the output of this role and ensure business alignment and impact. Be motivated by learning new skills and technologies.
  • Learn and understand a broad range of data resources and know when, how, and which to use and which not to at any given time.
  • Demonstrated analytical problem solving with adaptability to manage through ambiguity.
  • Excellent collaboration skills that promote a positive team environment by modeling behavior of continuous learning.
  • Ability to manipulate and analyze complex, high-volume, multi-dimensionality data from various sources.
  • Design, build, and maintain business reporting and dashboards, ensure data integrity and accuracy. 
  • Embody our culture and values