Data Scientist 2

Security 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 securityexpertise, 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 developstate-of-the-artmachine learning solutions that power real-time fraud and abuse detection and decision-making. Your work will directlyimpactMicrosoft's ability to prevent abuse, reduce financial and reputational risk, andoptimizekey 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.

Minimum Qualifications:

• Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field
• OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) or consulting experience.
• OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 2+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR equivalent experience.
• 1+ year(s) customer-facing, project-delivery experience, professional services, and/or consulting experience. 

Other Requirements:

Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include, but are not limited to the following specialized security screenings:

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.

Preferred Qualifications:

• Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results).
• OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results).
• OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR equivalent experience.
• Experience in gaming and e-commerce platform, and familiarity with related fraud vectors, such as refund abuse and market arbitrage. 
• Experience in risk scoring, bot mitigation, or anomaly detection systems. 
• Proficiency with cloud platforms such as Azure, and real-time inference systems. 
• Communication and collaboration skills, with the ability to influence across disciplines. 
• Proven ability to optimize detection systems for both technical and business metrics. 

Data Science IC3 - The typical base pay range for this role across the U.S. is USD $100,600 - $199,000 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $131,400 - $215,400 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: https://careers.microsoft.com/us/en/us-corporate-pay   

Microsoft will accept applications and processes offers for these roles on an ongoing basis.

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances.  We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request via the Accommodation request form.

Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.

• You will understand where toacquirethe data necessary for your project plan and use querying, visualization, and reporting techniques to describe that data.
• Explore data for key attributes and collaborate with others to perform data science experiments using established methodologies.

• Understand modeling techniques, select the correcttooland approach to completeobjectives, and evaluate the output for statistical and business significance.
• 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’llalso write efficient code for a specificfeature, anddevelop a workingexpertiseof proper debugging techniques.

• Understand device fingerprinting techniques,analyze the device attributes collectedfordevice fingerprinting, identify anomalous attributes within sessions as well as across sessions.
• Developtechniques to devise a unique device identifiergiven the device attributes.

• Understand theend to endprocessesof thereal timedecision platform, e.g., where theAPI is defined,what the API payload looks like, how wedo feature engineering,where we deploy our models,how wemonitor thedata flowandhow wemanage rules, among other things.

• Understand each customer’s business goalsandderive actionableinsightsvia data analysesto meet the goals.
• You will examine projects through a customer-oriented focus and manage customer expectationsregardingproject progress. You will alsopresentthefindingtobusiness stakeholders.

• Understandbest practices foridentifyinggrowth opportunitiesand endeavor to stay current with thelatest trends in machine learning, fraud detection, and abuse prevention.
• Understand how toshare knowledge and contribute to CFAR’sinnovationculture.