Senior Data Scientist

Microsoft’s Global Media and Partnerships team is a diverse, collaborative, solutions-oriented team committed to planning, activating and fiscally managing all paid media/advertising, strategic partnerships and agency relationships across Microsoft.  The team works across business groups to tie objectives, insights and innovation together to drive business impact through world-class media investment and measurement strategies. We are seeking a highly skilled and experienced Senior Data Scientist to join our dynamic team. The ideal candidate will have a background in data science, business intelligence, or business and financial analysis, along with significant experience in paid media measurement, optimization

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/Minimum 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.

Additional or 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.
• Media Specialty Experience

Data Science IC4 - The typical base pay range for this role across the U.S. is USD $117,200 - $229,200 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 $153,600 - $250,200 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 and processes offers for these roles on an ongoing basis.

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances.  We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request via the Accommodation request form.

Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.

Data Preparation and Understanding

Prepare and manage data for project plans, proactively detect changes, and communicate updates to senior leads. Develop usable data sets, contribute to data ethics and privacy policies, and engage with customers about data integrity and cleanliness.

Evaluating for Insight and Impact

Ensure models align with business goals, evaluate their effectiveness, design feedback methods, mentor engineers, and present findings to stakeholders.

Industry and Research Knowledge / Opportunity Identification

Provide technical feedback to the engineering team, identify business opportunities, propose collaborations, support strategy execution, leverage existing systems, share industry knowledge, and contribute to thought leadership and best practices.

Modeling and Statistical Analysis

Use machine learning solutions and algorithms to identify the best approach for objectives. Understand and apply modeling techniques, manage data quality, and communicate findings to stakeholders. Write scripts in T-SQL, U-SQL, KQL, Python, and R. Construct hypotheses, design experiments, analyze results, and communicate effectively. Develop scalable operational models with data engineering teams. Coach engineers on best practices. Understand Microsoft's Artificial Intelligence (AI) and Machine Learning (ML) tools. Break down complex topics for customers.

Help the Solution Architect and provide guidance on model operationalization that is built into the project approach using existing technologies, products and solutions, as well as established patterns and practices.

Other

• Embody our Culture and Values