Join us to build the future of Windows!
Windows 365 and Azure Virtual Desktop are fundamentally changing the nature of personal computing, pushing technology in the cloud to make remote experiences better, more secure, and easier to manage than local. Hand in hand, the pandemic has driven an explosion of remote and hybrid work. Windows 365 and Azure Virtual Desktop are growing explosively and, together with our 3p partners, enabling a wide variety of cloud experiences.
We are hiring a Senior Data & Applied Scientist with experience in advanced statistical data analysis and Machine Learning to work with high-impact professionals who are solving complex problems. You will have the rare opportunity to create intelligent Azure based Desktop Virtualization and Management platforms to help redefine how end user computing environments are managed and streamed to the end user. You'll enhance your communication skills as you share trends and innovative solutions, collaborating cross-functionally within the Microsoft ecosystem, including with product teams, research, and customer experience.
We value and encourage diversity in the belief that it leads to both great workplaces and great products. Our team embraces a growth mindset and encourages diverse viewpoints. We value personal and cultural experiences and strive for excellence. We offer a flexible work environment to help you succeed in creating innovative and responsible AI solutions.
Responsibilities
As a Senior Data Scientist, you will be responsible for creating and deploying AI solutions that are ethical, reliable, and enable our customers to create impact. Some of your key responsibilities will include:
- Engaging with stakeholders to understand and address their business problems with data-driven solutions.
- Have curiosity and apply analytical skills to dive deep into data to find key insights that impact the business.
- Writing clear, efficient code for multiple features, with expertise in modelling, coding, and debugging.
- Using your data science expertise to identify factors that influence project outcomes.
- Preparing re-usable datasets for modelling.
- Leveraging machine learning knowledge to select appropriate solutions for business objectives.
- Proficiency in big-data engineering concepts like CI/CD, Spark, Docker, Azure ML, and REST API development.
- Overseeing AI use case implementation and coaching cross-functional teams.
- Writing scripts and conducting controlled experiments with statistical analysis, communicating results to stakeholders.
- Partnering with data engineering teams for scalable operational models.
- Sharing industry insights via conferences and publications, staying updated on trends and contributing to thought leadership and intellectual property practices.
- Mentoring engineers and data scientists in best practices.
Qualifications
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, machine learning algorithms, predictive analytics 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, machine learning algorithms, predictive analytics 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, machine learning algorithms, predictive analytics and reporting results) OR equivalent experience.
- 2+ Years experience in Python, R or related ML programming language.
Preferred Qualifications:
- Familiarity with building and deploying large-scale AI solutions into production within a cloud environment.
- Regular interaction with internal and external stakeholders on large, complex projects.
- Excellent problem solving and data analysis skills, with expertise in developing or applying predictive analytics, statistical modeling, A/B experiments, data mining, or machine learning algorithms, especially at scale.
- Demonstrated communication skills and ability to collaborate in a multi-disciplinary team.
Data Science IC4 - The typical base pay range for this role across the U.S. is USD $112,000 - $218,400 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 $145,800 - $238,600 per year.
Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.
