Threat Protection team Privileged Identity Management
Digital thieves are getting more sophisticated and harder to detect and stop. Our enterprise customers are asking us to do more to protect their accounts from compromise and their data from theft - whether in Microsoft's cloud environments or their own datacenters. Proactive measures, including infrastructure security improvements, Privileged Identity Management and multi-factor authentication, are only part of the solution. The C+E Information and Threat Protection team is seeking Applied Machine Learning Engineers to help prevent the theft of our customer's digital assets using a range of behavioral modeling techniques. We are on the leading edge applying a unique combination of security research and machine learning that we call enterprise security intelligence. If you have a strong ML/statistics background and can roll up your sleeves to do the engineering work required to ship high quality ML models in production, this is a unique opportunity to tackle challenging problems in the fascinating
Develop high-performance machine learning systems for detecting abnormality, intrusion, fraud, masquerading, etc. Deliver end to end solutions to analyze data that originates from users, services, or other automated systems. Develop infrastructure as required to enable new experiences in enterprise security intelligence by deriving meaning from vast array of enterprise data about users and their activity. Build and operate enterprise class services. Actively engage with other teams across the company to identify security scenarios where machine learning/applied statistics can be used and guide
Basic Qualifications: 4+ years of experience developing production quality code in a professional software engineering role. 4+ years of educational or professional experience in applying machine learning and data mining techniques to real problems with copious amounts of data. Preferred Qualifications: Graduate degree in Computer Science or other quantifiable fields such as Engineering, Statistics, Mathematics, Machine Learning, Decision Science, Data Analytics, etc. Experience with very large-scale data processing/analysis (a.k.a. Big Data). Experience with Azure cloud services. Experience with