Microsoft Security aspires to make the world a safer place for all by reshaping security and empowering users, customers, and developers with a security cloud. The Central Fraud and Abuse Risk (CFAR) team specifically aims to protect Microsoft's customers and services from abuse and fraud by building innovative, intelligent, and scalable risk solutions.
Requirements
- 2+ years of Data Science or Machine Learning experience in handling high volumes of structured and unstructured data
- 2+ years of extensive programming experience in at least one of the following languages: C-Sharp, Python, or similar language
- 2+ years of data querying experience in SQL, Kusto (KQL) or similar languages
- Familiarity with ML tools & frameworks such as PySpark, Scikit-Learn, PyTorch etc.
- Familiarity with experiment design and applied machine learning for predicting outcomes in large-scale, complex datasets.
- Experience in cloud services with prior exposure to Big Data technologies is desirable but not required.
- Security and Fraud domain experience.
Responsibilities
- Contribute as a subject matter expert in machine learning, statistics, and experiment design.
- Drive fraud detection by researching evolving behaviors, identifying features with threat analysts, and applying scalable detection strategies.
- Collaborate cross-functionally with engineering and security teams to operationalize data and feature pipelines for new scenarios.
- Own model lifecycle by monitoring deployed detection models and continuously enhancing detection coverage and reliability.
Other
- Ability to meet Microsoft, customer and/or government security screening requirements are required for this role.
- Microsoft Cloud Background Check: This position will be required to pass the Microsoft background and Microsoft Cloud background check upon hire/transfer and every two years thereafter.
- Embody our culture and values
- Microsoft is an equal opportunity employer.
