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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_ _. _

Responsibilities

Job responsibilities:

+ You will understand where to acquire the 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 correct tool and approach to complete objectives, 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’ll also write efficient 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.

+ 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. You will also present the finding 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.

+ Understand how to share knowledge and contribute to CFAR’s innovation culture.

Embody our culture and values

Qualifications

Minimum Qualifications:

+ Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 2+ years related experience (e.g., statistics, predictive analytics, research)

+ OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research)

+ OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field OR equivalent experience.

+ 1+ year(s) customer-facing, project-delivery experience, professional services, and/or consulting experience.

+ 1+ years of experience in developing and deploying solutions using feature engineering, predictive analytics, machine learning, or statistical modeling.

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 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.

Applied Sciences 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 for the role until November 3rd, 2025.

\#MSFTSecurity

Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations (https://careers.microsoft.com/v2/global/en/accessibility.html) .