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Security represents the most critical priority 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 Identity Threat Detection and Response (ITDR) Security Research team leads advanced research in Identity protection, leveraging next-generation AI and cloud technologies. Our team comprises globally recognized experts in identity and cloud-related threats—highly skilled, passionate professionals committed to driving innovation and safeguarding customers in an ever-evolving. We are hiring a Principal Applied Scientist.
Job Responsibility:
Lead independently projects focused on AI / Agentic research applied to cybersecurity problems aiming to translate ideas and prototypes into concrete product advancements or novel capabilities
Productionize AI & ML: collaborate with engineering and product teams to productionize models, pipelines, and meet objectives for latency, throughput, and availability. Develop fine-tuning techniques for transformer models and establish benchmarks for accuracy, robustness, and performance to ensure reliable model delivery
Identify and integrate diverse data sources, develop deep expertise across them, and surface new patterns and opportunities—communicating clear, compelling, data driven stories visually and verbally
Analyze largescale datasets and build robust, scalable feature engineering pipelines in PySpark based environment
Partner with AI, Engineering and Data scientist teams to build machine learning systems that identify anomalies, account compromise, fraud, and identity threats, leveraging GenAI and graph based approaches
Collaborate across Threat Research, Engineering, and Product teams to define and instrument metrics that demonstrate product and business success (e.g Detection Efficacy, Coverage, Timetodetect)
Embody our culture and values
Requirements:
Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research)
Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience
Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience OR equivalent experience
Ability to meet Microsoft, customer and/or government security screening requirements
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 have:
Proven ability to design end-to-end data and feature pipelines (SQL, PySpark, Azure Data Studio) that ship robust, production ready ML models
Proven expertise in applying AI/ML systems and solutions to solve real cybersecurity problems
7+ years of hands-on experience with Spark/PySpark, Databricks, Azure ML, SQL/KQL, and strong programming skills in Python and/or C
2+ years experience presenting at conferences or other events in the outside research/industry community as an invited speaker
3+ years experience developing and deploying products or systems at multiple points in the product cycle from ideation to shipping
5+ years experience conducting research as part of a research program (in academic or industry settings)
Comfortable working with complex, high-dimensional, multisource data
excels at data wrangling, enrichment, and quality assurance to solve hard, real world problems
Works cross-functionally with Data Scientists, Threat Researchers, Engineering, and Product to define metrics, measure outcomes, and improve customer value. Communicates insights visually and verbally, telling clear, compelling, datadriven stories to drive decisions
Applied expertise in classification, prediction, anomaly detection, optimization, graph ML, and NLP. Experience with Generative AI (prompt engineering, RAG, finetuning, responsibleAI practices) is highly valued