Principal Data and Applied Scientist

Microsoft•Redmond, WA

About The Position

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. Our culture is centered on embracing a growth mindset, a theme of inspiring excellence, and encouraging teams and leaders to bring their best each day. In doing so, we create life-changing innovations that impact billions of lives around the world. Microsoft's Mission is to "Empower every person and every organization to achieve more" and Security is core to that statement. Microsoft's identity and authentication product portfolio, powered by Microsoft Entra, provide secure, seamless access to applications, devices, and data while protecting users from evolving cyber threats. With passwordless authentication, conditional access, and AI-driven security, Microsoft enables organizations to strengthen identity protection and simplify access management. Designed for enterprises and developers alike, Microsoft’s identity platform ensures compliance, scalability, and innovation in securing digital environments. The Identity Security team protects Microsoft Entra and other Microsoft products by preventing, detecting, and responding to security threats. We’re seeking a Principal Data and Applied Scientist to lead advanced analytics and machine learning initiatives that enhance security assurance across Microsoft Identity services. This role leverages predictive modeling, experimental design, and strategic influence to uncover emerging risks, accelerate mitigation, and optimize vulnerability management at scale. By enabling predictive insights and automating prioritization, you’ll help transform risk management and drive enterprise-wide security resilience. Interested? We’d love to hear from you! In alignment with our Microsoft values, we are committed to cultivating an inclusive work environment for all employees to positively impact our culture every day. 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.

Requirements

Doctorate 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 Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 7+ 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 10+ years data science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
OR equivalent experience.
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.

Nice To Haves

Experience in SQL-like query languages.
Experience in design & problem-solving skills with one or more programming languages, such as Python, Java, C# or C++.
Organizational, analytical, and data science skills with sound judgment.
Creative problem solver with the ability to tackle unprecedented challenges.
Excellent interpersonal skills for cross-team and cross-cultural collaboration.
Hands-on experience in building real-world systems, including data design, coding, and evaluation.
Outstanding communication skills to convey insights to senior leaders and diverse audiences.
Proven ability to lead large-scale collaborations across multiple teams.
Expertise in applying statistics, experimentation, and metrics to deliver actionable insights.
Background in cybersecurity with a track record of securing enterprise environments.
Solid foundation in Security Risk Engineering, including risk assessment and mitigation strategies.

Responsibilities

Risk Analytics & Automation: Lead development of predictive and prescriptive models to identify emerging security risks and prioritize mitigation.
Operationalize vulnerability risk scoring and automation to accelerate remediation across Microsoft Identity services.
Advanced Modeling & Machine Learning: Apply NLP and topic modeling (e.g., embeddings, LDA) to extract patterns from security case data for proactive risk identification.
Metrics & Experimental Design: Define and deliver metrics that measure security assurance impact and business value.
Design experiments and sampling strategies to validate models and continuously improve predictive accuracy.
Continuous Improvement: Monitor model performance, conduct error analysis, and iterate solutions to optimize vulnerability management at scale.
Drive automation that transforms risk management into a proactive, data-driven process.
Collaboration & Influence: Partner with engineers, product managers, and architects to embed analytics into governance workflows.
Communicate insights and recommendations clearly to senior leaders and cross-functional teams.
Translate strategy into measurable plans and report progress to leadership regularly.