Principal Data Scientist

We are inviting you to join the Microsoft Advertising Data Science Team.  Microsoft Advertising platform is the single stop shop for all monetization needs for Publishers and Advertisers globally. Our team manages the marketplace, which includes monitoring business metrics, defining metrics, building analytical & experimentation frameworks, and enabling leadership to make data driven decisions. The team works across Engineering, Product and Business to address complex data science problems across users, advertisers, and publishers. 

We are looking for high-energy, creative data scientist who is willing to work in a dynamic environment to solve real life day to day problems, leveraging data science techniques. You will enjoy and be successful in this role if you are curious and willing to challenge the status quo and come up with data driven solutions to ambiguous problems. 

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 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 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.
• 5+ years of experience in at least one of programming languages like Python/R/SQL/C#/Java/C++. 

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. 
• Demonstrated experience with machine learning modeling and/or experimentation
• Great organizational, analytical, data science skills and intuition.  
• Fantastic problem solver: ability to solve problems that the world has not solved before.  
• Interpersonal skills: cross-group and cross-culture collaboration.  
• Experience with real world system building and data collection, including design, coding and evaluation.   
• Communication to be able to communicate insights to senior leaders. 

Data Science IC5 - The typical base pay range for this role across the U.S. is USD $137,600 - $267,000 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 $180,400 - $294,000 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 October 13, 2024.

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.

As a Principal Data Scientist in the team, your major responsibilities include: 

• Measurement: Define, invent, and deliver metrics which accurately measure user and business value across various products and marketplace components. 
• Modeling: Design, create and implement machine learning (ML) models and frameworks to forecast and predict market response to changes.  
• Product Iteration: Interpret the results of analyses, validate approaches, and learn to monitor, analyze, and iterate to continuously improve. 
• Cooperation: Partner effectively with program management, engineers, and other areas of the business across our Consumer online business. 
• Influence: engage with stakeholders to produce clear, compelling, and actionable insights and data-science driven workflows that influence product and service improvements. 
• Make independent decisions for the team and handle difficult tradeoffs. 
• Translate strategy into plans that are clear and measurable, with progress shared out monthly to stakeholders.