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Senior Data Scientist

ExtraHop

Skills

Required

  • machine learning
  • data science
  • anomaly detection
  • AI
  • Python
  • SQL
  • machine learning libraries
  • experimental design
  • model evaluation

Preferred

  • cybersecurity
  • fraud detection
  • abuse detection
  • Network Detection and Response / network protocols / threat detection / incident investigation
  • evaluating models
  • cloud platforms
  • AWS / GCP
  • error analysis
  • AI-based

ExtraHop, a leading cybersecurity company, as a Senior Data Scientist. In this role, you will analyze large-scale network telemetry to identify behavioral patterns and anomalies associated with malicious activity.

Responsibilities

  • You will design, develop, and refine machine learning and AI-based methods that support ExtraHop's products.
  • Additionally, you will conduct exploratory data analysis, feature engineering, model development, and error analysis using complex, high-volume datasets.
  • You will also provide technical leadership and mentorship to other data scientists and communicate findings and recommendations to technical stakeholders and product leaders.
  • Analyser des télémetries réseau à grande échelle pour identifier des modèles de comportement et des anomalies.
  • Concevoir, développer et affiner des méthodes basées sur l'apprentissage automatique et l'IA pour soutenir les produits d'ExtraHop.
  • Développer des méthodes d'évaluation appropriées pour les données de cybersécurité, y compris les ensembles de données déséquilibrés.
  • Experience collaborating with software engineers to integrate data science methods into production systems

Requirements

  • Strong proficiency in Python and SQL, experience with common data science and machine learning libraries, and the ability to write maintainable, tested, and reviewable code
  • Strong problem-solving skills, intellectual curiosity, and a track record of independently owning complex technical work
  • Bachelor’s degree in Data Science, Computer Science, Mathematics, or another quantitative discipline, or equivalent practical experience
  • Strong foundation in statistics, experimental design, machine learning, and model evaluation
  • 7+ years of professional experience in data science, including developing and evaluating machine learning models for real-world use cases, defining meaningful success metrics, and conducting rigorous offline and online evaluations
  • Excellent written and verbal communication skills, including the ability to explain technical findings, uncertainty, and tradeoffs to varied audiences
  • Experience working with incomplete, noisy, or highly imbalanced data; performing detailed error analysis; and identifying the causes of false positives and false negatives
  • Experience with time-series analysis, anomaly detection, actuarial modeling, clustering, graph analytics, or unsupervised and semi-supervised learning
  • Experience with generative AI, large language models, agentic systems, or other emerging AI techniques

Preferred

  • Master’s degree or Ph.D. in Data Science, Computer Science, Mathematics, or another quantitative discipline
  • Experience applying data science or machine learning to cybersecurity, fraud detection, abuse detection, anomaly detection, or another adversarial domain
  • Familiarity with Network Detection and Response, network protocols, threat detection, or incident investigation
  • Experience evaluating models in domains where positive examples are rare, labels are incomplete, and the underlying behavior changes over time
  • Familiarity with cloud platforms such as AWS or GCP

Pay

USD 165,000 - 180,000