Senior Data Scientist

Microsoft AI (MAI) creates innovative AI-powered and personalized web experiences in Microsoft Windows, Edge & Bing, that inform, entertain, add value, save money, and breathe productivity into the life and work of millions of customers. MAI makes the web work for our consumers, advertisers, and publishers in a safe environment where everyone can get informed, entertained, save money and thrive!  

The Feeds & Verticals organization builds tools to connect people to content that matters. We aim to make Microsoft consumer products the content powerhouse for every person on the planet by delivering personalized experiences. We are looking for a highly motivated and experienced Senior Data Scientist to join our Growth and Analytics team. 

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.

Required Qualifications:  

• Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ 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 3+ 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 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)

  • OR equivalent experience.

Preferred Qualifications:  

• Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ 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 5+ 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 7+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results))

  • OR equivalent experience.

• Experience with Power BI and SQL is advantageous.

Data Science IC4 - The typical base pay range for this role across Canada is CAD $108,100 - CAD $199,700 per year.

Find additional pay information here:


Microsoft will accept applications for the role until January 1, 2025.

In this role, you will have ownership of high-visibility initiatives across our portfolio and will lead the generation of insights that drive our business. Expect to work with a host of engaged stakeholders who value your skills and consider you thought partners in driving the business!  

Data & Analytics:  

• Collaborating with stakeholders to identify and align on business-critical metrics, their definitions, sources, and interpretations.  
• Gathering, processing, and interpreting data from various sources while ensuring data quality and integrity.  
• Analyzing large datasets to identify patterns, trends, and content performance to provide ongoing reports on the relevance and quality of our products.  
• Utilizing experimentation results to iterate and fine-tune models, ensuring continuous improvement and impact on key business metrics. 

Collaboration & Communication:  

• Working closely with product managers, engineers, and other stakeholders to understand business requirements and translate them into actionable data science initiatives.  
• Effectively communicating findings, insights, and recommendations to both technical and non-technical stakeholders, enabling informed decision-making. 
• Sharing and discussing findings with senior leadership to shape product strategy and investments.