Principal Data Science Manager

Microsoft

About The Position

Microsoft aspires to help our customers achieve their own AI and digital transformation, leveraging the power of Microsoft cloud solutions and services, to support our mission of empowering every person and every organization on the planet to achieve more. Key to our aspirations, the Customer Solutions Area (CSA) organization plays a critical role, operating at the center of our Commercial business, to define, land and operate 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, and in every market. Within the CSA organization, the Innovation and Acceleration Business Insights team works across our Commercial Solution Areas, and across Microsoft’s Customer and Partner Solutions and Marketing organizations, providing data and insights to accelerate the growth of our business. As Principal Data Science Manager, we are looking for an exceptional leader and collaborator to lead a team of data scientists and data engineers, guiding the development and maintenance of our data platform to enable high scale, big data, analytics and AI capabilities while also delivering actionable business insights, reporting and new capabilities (i.e. sales insights agents) to our Commercial Solution Area Corporate team as well as our worldwide sales organization. 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.

Requirements

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.

Nice To Haves

Experience working in the software and cloud services industry, market shaping trends such as AI and routes to market.
Experience working in a variety of customer segments, industry verticals, and their corresponding sales engines with demonstrated success in driving revenue growth in new business models
Experience identifying opportunities and alternatives while influencing a large team to execute on them (with demonstrated results) in a global matrix.
Experience steering initiatives and foster a collaborative environment by managing cross-functional teams, creatively resolving issues, and driving change. This includes developing business relationships and promoting adaptive leadership to navigate complex organizational dynamics.

Responsibilities

People Management: Managers 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 and develop everyone’s capabilities and aspirations. Invest in the growth of others.
Metrics Definition, Reporting and Analysis
Oversee and advise others on conceptualizing, defining, driving alignment on, and evangelizing foundational metrics and dashboards to democratize data-driven decision-making and look beyond existing opportunities to make improvements.
Steers partnerships with internal customers to define and translate vague, complex, and/or large-scale business problems into data-verifiable hypotheses and ensure team objectives are connected to relevant key performance indicators (KPIs).
Refines methods for analyzing and interpreting internal, highly complex, unstructured and/or structured data, ensuring teams consider external sources or cross-line-of-business information where necessary to assess business health and understand what drives business outcomes and/or drive business outcomes at the organizational level.
Provides input on best practices for developing and employing models and causal analyses (e.g., panel analysis, A/B testing) to determine what drives metric relationships and lead the creation of innovative, actionable insights within highly complex product domains.
Lead the team to develop classical Power BI reporting as well as agentic UI to meet the needs of internal constituencies.
Strategic Analysis and Opportunity Identification
Leads team on recommending improvements to standards for performing complex data analyses exploring potential and/or proposed opportunities for improved growth, innovation, and efficiency, potentially impacting business strategy.
Shapes expectations for creating compelling, data-centric stories and recommendations based on analytical findings, leading others to heavily influence and shape strategic direction and decision-making.
Drives a strategy to maintain a secure, highly productive and cost-effective Data and AI platform to maintain and improve high productivity standards of the Data Scientists in the team.
Drives innovation (customer 0) by identifying opportunities to leverage AI and new technologies as they become available. Encourage and create opportunities for continuous learning.
Responsibly manage vendor budget and Azure subscription costs to achieve business goals.
Translating Business Needs into Data Solutions
With a solid grasp of cloud consumption, ABS business and the MCEM sales process, you will coach the data science team and internal stakeholders to interpret business context and convert strategic objectives into clear analytical frameworks. With a strong focus on driving business performance, you will ensure insights remain relevant to evolving business priorities and are delivered in concise, actionable terms that drive impact across diverse stakeholder groups.