Director, Applied Data Science
Microsoft
Director, Applied Data Science
Redmond, Washington, United States
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Overview
The Azure, Windows, and Industry Monetization (“AWIM”) organization is a big picture team at our core that encourages a diverse and inclusive culture. We are respectful, collaborative, honest, accountable, and caring. Employees on the team can expect to have opportunities to grow their own experiences and career while shaping the future of the major businesses with data-informed strategies.
We are growth strategists who enable the Microsoft mission by creating durable profit growth through high-impact monetization strategies, packaging, and pricing. Our charter is significant and spans key growth engines for the company including all Azure solution areas, Windows client and cloud offerings, and our Education and industry offerings and programs.
You’ll be working in the Azure, Windows, and Industry Monetization organization in the group that is focused on global Azure growth and yield management. 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.
We are seeking an experienced and dynamic Director, Applied Data Analytics and Data Science to lead and grow our data-driven decision-making capabilities. The scope of this role spans from core infrastructure strategy through regional Datacenter pricing decisions. This individual will oversee a team of skilled data scientists and business strategists, driving the strategic vision for our data analytics and science initiatives. The Director will play a pivotal role in shaping our data strategy, ensuring that our data analytics efforts align with business goals and deliver measurable impact across the organization.
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. 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.
Qualifications
Required/Minimum 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.
- 3+ years people-management experience.
- 3+ years experience working directly with data tools and technologies such as Python, R, SQL, and data visualization tools like Tableau or Power BI.
- 2+ years experience implementing, analyzing, and optimizing web and application telemetry.
- 2+ years experience working directly within data analytics, machine learning, and statistical modeling.
Additional or 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.
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 11, 2025.
Responsibilities
- Leadership and Strategy:
- Lead, mentor, and manage a team of data professionals and business planners fostering a collaborative and innovative team culture.
- Develop and execute a strategic roadmap for data analytics and data science that aligns with the company’s business objectives.
- Develop and execute strategies to optimize yield and maximize ROIC by optimizing product pricing, product offerings, and packaging.
- Lead the design and implementation of data-driven frameworks to evaluate and improve business performance.
- Advocate for data-driven decision-making across the organization, promoting industry standards in data analysis, modeling, and governance.
- Stay abreast of industry trends and advancements in data science and analytics, applying relevant innovations to the team’s work.
- Collaboration and Cross-Functional Partnership:
- Work closely with the Data Engineering team to ensure that data infrastructure supports the needs of analytics and modeling initiatives.
- Collaborate with Engineering, Sales, Marketing, Product, Planning and other key business units to deliver innovative pricing, packaging, and product solutions.
- Partner with executive leadership to translate complex data analyses into clear, actionable insights and strategies.
- Lead the team in developing predictive models, customer segmentation, and other data-driven strategies to improve ROIC.
- Project Management and Execution:
- Oversee the design, implementation, and delivery of analytics projects, ensuring they are completed on time, within scope, and deliver impactful results.
- Prioritize and manage multiple projects simultaneously, balancing the needs of different business units with available resources.
- Ensure data quality, integrity, and security across all analytics projects, adhering to industry standards in data governance.
- Performance Monitoring and Reporting:
- Establish key performance indicators (KPIs) to measure the effectiveness of analytics and data science initiatives.
- Develop and maintain dashboards, reports, and presentations that communicate insights to stakeholders at all levels of the organization.
- Regularly review and refine models, methodologies, and processes to ensure they continue to deliver value and drive business performance.
- Other