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Microsoft’s Identity organization secures hundreds of millions of daily signins and protects missioncritical services at global scale. We’re hiring a Senior Data Scientist to advance adaptive threat detection at the edge and resilience of origin services—designing models that detect and mitigate abusive patterns in real time, improving customer safety and service reliability.
Job Responsibility:
Design, build, and operate machine-learning–based detections to prevent fraud and abuse across Microsoft Identity services
Lead signal and model design by defining features, labels, heuristics, and training approaches using supervised and unsupervised techniques
Analyze large-scale authentication, access, and traffic data to identify emerging abuse patterns and translate them into automated detections
Productionize models for low-latency online scoring, implementing guardrails, dynamic thresholds, and safety mechanisms to minimize customer impact
Design and analyze experiments (A/B tests, holdouts) to evaluate detection effectiveness and quantify tradeoffs such as false positives and false negatives
Define and monitor key metrics and dashboards to track model performance, data quality, and drift, enabling rapid iteration and response
Partner cross-functionally with engineering, product, and security teams to harden pipelines, align on success metrics, and support incident response and investigations
Document designs and findings clearly and contribute to reviews, readiness checks, and continuous improvement of detection systems
Requirements:
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)
Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience
Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience
equivalent experience
Ability to meet Microsoft, customer and/or government security screening requirements
Microsoft Cloud Background Check
Nice to have:
MS/PhD in computer science, machine learning, statistics, or quantitative domain
Expertise in Python (or Scala/R) and ML tooling (e.g., PyTorch, scikitlearn, Spark)
strong SQL skills for largescale analysis
Hands on experience with anomaly detection, timeseries, class imbalance techniques, and online evaluation in realtime systems
Demonstrated strength in experiment design (A/B, CUPED or equivalent), causal inference basics, and metric stewardship
Proven ability to collaborate across engineering, product, and operations
clear written and verbal communication with executive and technical audiences
Background in security, antiabuse, fraud prevention, threat intelligence or traffic defenses at internet scale
Experience with streaming and telemetry platforms (e.g., Kafka/Event Hubs), feature stores, and MLOps (training, deployment, monitoring)
Familiarity with edge/proxy concepts (rate limiting, backpressure, routing), and reliability practices (SLOs, error budgets)