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Microsoft Principal Data Scientist 
Canada, British Columbia, Vancouver 
760981328

04.02.2025


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 techn
    • 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 te
    • OR equivalent experience.
  • 5+ years customer-facing, project-delivery experience, professional services, and/or consulting experience.

Preferred Qualifications:

  • Previous web analytics, product analytics and or content analytics experience.
  • Knowledge of Ads ecosystem, content and online shopping metrics.
  • Interpersonal communication and ability to leverage the data to tell a story.
  • Demonstrated stakeholder management ability including effective prioritization, clear and concise communication, and delivery of actionable data-driven insights.
  • Knowledge on big data processing from raw events to metrics and insights (PySpark/Scala is preferred).

Data Science IC5 - The typical base pay range for this role across Canada is CAD $135,800 - CAD $253,000 per year.

Find additional pay information here:
Microsoft will accept applications for the role until February 8, 2025.


Responsibilities

Your responsibilities will include:

  • Build metrics system to measure Business Health and quick identify the root cause when metrics moves.
  • Collaborating with cross-functional teams to understand features, estimate impacts and drive the engagement improvements based on insights from big data.
  • Enhance products by evaluating performance metrics and user feedback. Develop self-service dashboards and reports for various stakeholders using reporting platforms.
  • Analyzing large datasets to identify patterns, trends, and content performance to improve the relevance and quality of our recommendation systems.
  • Conduct business modeling to identify growth opportunities and initiate projects with a positive long-term ROI.
  • Designing and conducting A/B tests to evaluate algorithm performance and proposing iterative improvements based on the results.
  • Effectively communicating findings, insights, and recommendations to both technical and non-technical stakeholders, enabling informed decision-making.