Senior Applied & Data scientist

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.

The Defender Experts (DEX) Research team is at the forefront of Microsoft’s threat protection strategy, combining world-class hunting expertise with AI-driven analytics to protect customers from advanced cyberattacks. Our mission is to move protection left—disrupting threats early, before damage occurs—by transforming raw signals into intelligence that powers detection, disruption, and customer trust. We’re looking for a passionate and curious Data Scientist to join this high-impact team. In this role, you'll partner with researchers, hunters, and detection engineers to explore attacker behavior, operationalize entity graphs, and develop statistical and ML-driven models that enhance DEX’s detection efficacy. Your work will directly feed into real-time protections used by thousands of enterprises and shape the future of Microsoft Security. This is an opportunity to work on problems that matter—with cutting-edge data, a highly collaborative team, and the scale of Microsoft behind you.

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

• Understand complex cybersecurity and business problems, translate them into well-defined data science problems, and build scalable solutions.
• Design and build robust, large-scale graph structures to model security entities, behaviors, and relationships.
• Develop and deploy scalable, production-grade AI/ML systems and intelligent agents for real-time threat detection, classification, and response.
• Collaborate closely with Security Research teams to integrate domain knowledge into data science workflows and enrich model development.
• Drive end-to-end ML lifecycle: from data ingestion and feature engineering to model development, evaluation, and deployment.
• Work with large-scale graph data: create, query, and process it efficiently to extract insights and power models.
• Lead initiatives involving Graph ML, Generative AI, and agent-based systems, driving innovation across threat detection, risk propagation, and incident response.
• Collaborate closely with engineering and product teams to integrate solutions into production platforms.
• Mentor junior team members and contribute to strategic decisions around model architecture, evaluation, and deployment.
  
  

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Statistics, Applied Mathematics, Data Science, or a related quantitative field
• 6+ years of experience applying data science or machine learning in a real-world setting, preferably in security, fraud, risk, or anomaly detection
• Proficiency in Python and/or R, with hands-on experience in data manipulation (e.g., Pandas, NumPy), modeling (e.g., scikit-learn, XGBoost), and visualization (e.g., matplotlib, seaborn)
• Strong foundation in statistics, probability, and applied machine learning techniques
• Experience working with large-scale datasets, telemetry, or graph-structured data Ability to clearly communicate technical insights and influence cross-disciplinary teams
• Demonstrated ability to work independently, take ownership of problems, and drive solutions end-to-end
  
  

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.