Senior Data Scientist
ExtraHop
- United States
- Senior Level
- 7+ years
- Bachelor's degree
- Posted
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
