We are looking for a Senior Data Scientist to come and join the Power Apps Interface team. Traditional software development is being disrupted by low-code app building tools and AI-infused Copilots. At Microsoft, the Power Apps team sits at the apex of this disruption. Our mission is to empower citizen app makers and professional developers alike with tools for building modern, intelligent, and powerful business applications.  As Microsoft CEO Satya Nadella said, "With our Power Platform, we are enabling anyone with a big idea and the passion to make a difference to maximize their impact and transform their organization for the better."     

If helping define the future of AI-first applications seems exciting, join the Power Apps Interface team, where we focus on infusing AI capabilities into business application experiences. Our goal is to develop the best-in-class controls that are both visually delightful and empowered by an intelligent Copilot.  If you're ready to accelerate your career and contribute to the digital transformation ambitions of organizations worldwide, join us in driving the AI revolution. Together, we can empower every individual to do more!    

Responsibilities

As a Senior Data Scientist, your core mission will be partnering with the wider team to make sure data, data science (DS), and artificial intelligence (AI) are used effectively, efficiently, and responsibly. We are looking for candidate who love answering questions using data. You will lead by example by applying AI, machine learning, and data science to further Copilot and agentic product enhancements.  

• Working closely with a variety of teams like partner data science, engineering, and UX teams.  

• Developing ML models and solutions using classical algorithms as well as foundation models.  

• Deploying these solutions into production.  

• Measuring and reporting success, using A/B and shadow experiments, creating dashboards and reports as necessary.  

• Using data to answer business questions like potential impact and usage.  

• Customer journey, NSAT, churn, retention analysis.  

• Presentation of work in the team and at Microsoft, such as during Town Halls and MLADS.  

Qualifications

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. 

Other Requirements:  

• Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings: Microsoft Cloud Background Check:  

• This position will be required to pass the Microsoft background check.    

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. 

• Publication history in respected data mining and AI conferences and journals.  

• Deep understanding of statistics and statistical theory. 
• Have taken qualifying courses on machine learning concepts including, and not limited to: decision trees and forests, gradient descent, logistic regression, deep neural networks, etc.  

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 for the role until September 17, 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. 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.