Senior Data Scientist — AI for Cybersecurity

CrowdStrike; Idaho; On-site; USD 140,000 - 215,000; Full time

Benefits offered by this job

Equity awards

Professional development opportunities

Job summary

CrowdStrike is seeking a Senior Data Scientist to join the NGSIEM Agentic AI team. You will design, build and deploy advanced AI systems that analyze and prioritize millions of security events per second, enabling rapid threat identification and response.

You will own complex AI challenges and shape the next generation of AI-powered security operations. You will lead architecture for retrieval, ranking, vector search, and anomaly detection, while driving innovations in LLM-driven discovery, and

Qualifications

• 8+ years of experience building and scaling large-scale AI/ML, search, retrieval, ranking in the cybersecurity space.
• MS, PhD, or equivalent industry experience in Computer Science, Statistics, Physics, or related quantitative discipline.
• Deep expertise in semantic retrieval, vector search, ranking systems, NLP/LLMs, RAG architectures, and agentic AI systems.

Responsibilities

• Lead architecture for large-scale retrieval, ranking, vector search, RAG, and anomaly detection at enterprise scale.
• Own end-to-end AI/ML architecture including data pipelines, feature engineering, model development, deployment, monitoring.
• Define evaluation methodologies and partner with product, engineering, security, and operations to deliver scalable AI solutions.

Skills

Python

Go

SQL

Spark

Vector search

NLP/LLMs

Experience in cybersecurity

Education

MS/PhD in CS/Stats/Physics

Tools

Kubernetes

Kafka

S3

Iceberg

Parquet

Job description

CrowdStrike is seeking a Senior Data Scientist to join the NGSIEM Agentic AI team. You will design, build and deploy advanced AI systems that analyze and prioritize millions of security events per second, enabling rapid threat identification and response.

You will own complex AI challenges and shape the next generation of AI-powered security operations. You will lead architecture for retrieval, ranking, vector search, and anomaly detection, while driving innovations in LLM-driven discovery, and