New 
Data Scientist II
 Microsoft | |
 United States, Washington, Redmond | |
 May 10, 2025 | |
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OverviewSecurity is a top priority in a world facing evolving digital threats and increasing regulatory expectations. Microsoft Security's mission is to make the world a safer place by delivering end-to-end, simplified solutions that protect users, organizations, and developers. We accelerate Microsoft's broader mission by securing our platforms, products, and cloud services across internal and external ecosystems. 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 Data Scientist II 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. This Onsite Position is located at our Microsoft office in Redmond, Washington. Relocation support will be provided, and successful candidates will need to relocate or reside within 50 miles of the field location.
ResponsibilitiesAs a Data Scientist II, you will:Understand where to acquire the data necessary for your project plan and use querying, visualization, and reporting techniques to describe that data. You'll also explore data for key attributes and collaborate with others to perform data science experiments using established methodologies. Understand modeling techniques, select the correct tool and approach to complete objectives, and evaluate the output for statistical and business significance. You'll analyze model performance and incorporate customer feedback into its evaluation. Understand the current state of the industry, including current trends, so that you can contribute to thought leadership best practices. You'll also write code for a specific feature, and develop a working expertise of proper debugging techniques. Understand device fingerprinting techniques, analyze the device attributes collected for device fingerprinting, identify anomalous attributes within sessions as well as across sessions. You will develop techniques to devise a unique device identifier given the device attributes. Understand the end to end processes of the real time decision platform, e.g., where the API is defined, what the API payload looks like, how we do feature engineering, where we deploy our models, how we monitor the data flow and how we manage rules, among other things. Understand each customer's business goals and derive actionable insights via data analyses to meet the goals. You will examine projects through a customer-oriented focus and manage customer expectations regarding project progress and will present the findings to business stakeholders. Understand best practices for identifying growth opportunities and endeavor to stay current with the latest trends in machine learning, fraud detection, and abuse prevention. | |