Microsoft is a company where passionate innovators come to collaborate, envision what can be and take their careers further. This is a world of more possibilities, more innovation, more openness, and the sky is the limit of thinking in a cloud-enabled world.Microsoft’s Windows Cloud Experiences (WCX) engineering team is 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. Windows 365 and Azure Virtual Desktop services are growing explosively and, together with our partners, enabling a wide variety of cloud experiences. 

The Data Science & Analytics team’s mission is to enable WCX services’ customer growth, high customer satisfaction and COGS (Cost of Goods Sold) reduction by leveraging data, insights and AI (Artificial Intelligence)  solutions. We develop increasingly powerful machine learning capabilities to cost-effectively manage VMs hosted on our platform while keeping the user experience at the best. 

We are seeking a driven Data Scientist with experience working with structured and unstructured data. In this role, you will be responsible for delivering deep analytical insights to drive business success as well as productizing ML (Machine Learning) models to help drive growth, efficiency, and satisfaction of our products. This role requires close collaboration with other disciplines.  

This opportunity will allow your professional growth and development in the rapidly evolving field of AI/ML. You will work in a dynamic and innovative environment that encourages creativity and continuous learning. This is a unique opportunity to join a collaborative team of data scientists and engineers focused on cutting-edge projects and contribute to a strategic initiative with potential to have significant impact on the business. Our culture is more like a startup – we will do what is necessary to help customers be successful, move fast, and have fun building meaningful products and services! 

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.

Responsibilities

• Develop and ship machine learning based products and features. 

• Work on machine learning (ML) projects across various domains like natural language processing (NLP), Causal Inference, Time Series Forecasting, Recommendation Systems, and harness Large Language Models (LLMs) to deliver AI solutions. 

• Work with a team of high-performing analytics, data science professionals, and cross-functional teams to identify business opportunities and develop algorithms and methodologies to address them. 

• Conduct in-depth and rigorous data science research, model improvement, advanced experiments, observational causal studies to quantify the cause and effect in the systems. 

• Communicate with clarity to drive action and results. 

• Embody our culture and values. 

Qualifications

Required Qualifications

• Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field

OR equivalent experience.

• Experience with at least one programming language (eg. R, Python, or Scala/Spark )

Preferred Qualifications

• Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field

o OR

• Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)

                     OR equivalent experience.

• Experience developing and deploying live production systems, as part of a product team.
• Experience with at least one programming language (eg. R, Python, or Scala/Spark )

• Research experience (publications) at least one of the following areas is preferred - machine learning, deep learning, NLP (Natural Language Processing) , data mining, information retrieval.
• Experience working with LLM (Large Language Model)/SLM (Small Language Model)

Data Science IC2 - The typical base pay range for this role across the U.S. is USD $81,900 - $160,200 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 $105,600 - $174,600 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 July 30, 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.

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