Data Analytics
 Microsoft | |
 United States, North Carolina, Charlotte | |
 Feb 20, 2025 | |
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OverviewMicrosoft Securityaims to make the world a safer place for everyone. Our mission is to reshape security and empower every user, customer, and developer with a security cloud that delivers end-to-end, simplified solutions. The Central Fraud and Abuse Risk (CFAR) team is seeking a Data Analytics professional who will help us protect our customers and our company by eradicating fraud and service abuse across the Microsoft ecosystem. Our goal is to minimize financial and reputational harm by preventing, detecting, and addressing fraud. As a CFAR Data Analytics professional, your role involves understanding the business needs of internal stakeholders and integrating that knowledge with a deep understanding of the data landscape. You'll focus on understanding and harnessing diverse data sources, conducting thorough analyses, and deriving actionable and visually intuitive insights that drive our mission forward through leveraging the power of generative AI and the action-orientation of agentic AI.
ResponsibilitiesIdentify appropriate analytical techniques, conduct analyses, and provide actionable recommendations to address business questions at scale, using the latest available tools Collaborate across teams to ensure consistency in data sources, methods, models, tools, and business priorities, to build reusable and sharable improvement techniques Develop experiments and prototypes using a deep understanding business process and underlying data structures to drive meaningful recommendations for actions to CFAR's fraud reduction remit Translate the work of our data scientists' custom machine learning models and generative AI into intuitive, context-sensitive insights for internal stakeholder decision-making Analyze and implement new AI tools and algorithms to help simplify fraud pattern recognition and human understanding to enable CFAR solutions that better address fraud Stay current on Microsoft data privacy and security standards as well as regulatory and ethical requirements to ensure proper data handling and compliant analytic solutions | |