Microsoft Azure is the foundation for cloud workloads supporting millions of customers across a vast array of cloud native and heterogeneous architectures. Attackers are relentless in their attempts to find a way to compromise all manner of computing infrastructure, and cloud services such as Azure are also in their crosshairs. Do you want to take a major leadership role in a team dedicated to protecting Azure from sophisticated attackers?
At Microsoft Security, our mission is to make the world a safer place for all. The Threat Protection Research Team is a global, multidisciplinary organization of engineers, data scientists, security researchers, and program managers. With trillions of signals from millions of endpoints, we have an unparalleled view of the threat landscape, enabling us to develop deep expertise in attacker techniques and use that knowledge along with the latest technology to stop it.
We are looking for a Senior Data Scientist to apply their deep knowledge of machine learning and AI to detect attacks on Azure. This person should have a deep understanding and practical experience with the latest advancements in AI, understand modern cloud computing architectures, and be able to oversee the creation of data-driven solutions in a large-scale, operational organization supporting millions of customers. Are you up for this challenge?
Our culture is centered on embracing a growth mindset, a theme of inspiring excellence, and encouraging teams and leaders to bring their best each day. In doing so, we create life-changing innovations that impact billions of lives around the world.
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/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 Cloud Background Check upon hire/transfer and every two years thereafter.

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.
• Experience with Spark and tools such as Azure Synapse Analytics, Microsoft Fabric, Databricks, or similar
  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
  Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: https://careers.microsoft.com/v2/global/en/us-corporate-pay.html
  Microsoft will accept applications for the role until May 25, 2024.
  

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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

• Work closely with security researchers, program managers, other data scientists, and engineering teams to help implement a data-driven strategy for detecting attacks against Azure
• Perform exploratory data analysis on massive data sets generated from telemetry
• Perform experiments to determine the most effective approaches to detect attacks, including application of supervised, unsupervised, and anomaly detection machine learning techniques
• Train and deploy machine learning models to production environments to support detecting new attacks on Azure
• Implement machine learning pipelines for continuous retraining and evaluation of model performance
• Participate in planning how we should measure the most pressing threats to the Azure environment and guiding others in the creation and improvement of these metrics.
  Embody our Culture and Values