Applied Scientist

Microsoft hybrid • Redmondfull_time

Security represents the most critical priorities for our customers in a world awash in digital threats, regulatory scrutiny, and estate complexity. Microsoft Security aspires to make the world a safer place for all. We want to reshape security and empower every user, customer, and developer with a security cloud that protects them with end to end, simplified solutions. The Microsoft Security organization accelerates Microsoft’s mission and bold ambitions to ensure that our company and industry is securing digital technology platforms, devices, and clouds in our customers’ heterogeneous environments, as well as ensuring the security of our own internal estate.  

The Central Fraud and Abuse Risk (CFAR) team builds innovative, intelligent, and scalable risk solutions that protect Microsoft’s customers and services from abuse and fraud. We combine deep security expertise, high-quality data, and engineering excellence to enable real-time and strategic decision-making. We value inclusivity, experimentation, collaboration, and a growth mindset.  We are looking for a Applied Scientist who is passionate about machine learning, eager to innovate, and committed to protecting users through data-driven technologies. In this role, you will develop state-of-the-art machine learning solutions that power real-time fraud and abuse detection and decision-making. Your work will directly impact Microsoft's ability to prevent abuse, reduce financial and reputational risk, and optimize key performance indicators (KPIs) across our risk ecosystem.  

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.