Sr. Data Scientist (hybrid)

CrowdStrike CrowdStrike · Enterprise · Sunnyvale, CA

Senior Data Scientist role focused on building and scaling advanced AI systems for cybersecurity, specifically within the NGSIEM Agentic AI team. The role involves leading the architecture and technical strategy for large-scale retrieval, ranking, vector search, RAG, and anomaly detection systems, driving innovation in LLMs and autonomous AI workflows, and owning end-to-end AI/ML architecture from data pipelines to deployment and monitoring. The position requires deep expertise in semantic retrieval, LLMs, RAG, and agentic AI, with a strong emphasis on operational excellence, scalability, and delivering measurable business impact in a production environment.

What you'd actually do

  1. Lead the architecture and technical strategy for large-scale retrieval, ranking, vector search, RAG, and anomaly detection systems operating at enterprise scale.
  2. Drive innovation across LLMs, AI-powered discovery, personalization, and autonomous AI workflows.
  3. Define the future direction of AI-driven reasoning, ranking and investigation capabilities across the platform.
  4. Own end-to-end AI/ML architecture, including data pipelines, feature engineering, model development, deployment, monitoring, evaluation, and continuous improvement.
  5. Establish scalable architecture patterns, engineering standards, experimentation frameworks, and operational best practices across multiple teams.

Skills

Required

  • 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 a related quantitative discipline
  • Deep expertise in semantic retrieval, vector search, ranking systems, recommendation systems, NLP/LLMs, RAG architectures, and agentic AI systems
  • Strong understanding of retrieval and ranking trade-offs, experimentation methodologies, model evaluation, and operational excellence
  • Experience operating large-scale production systems with demanding latency, scalability, reliability, and cost requirements
  • Proven track record of delivering measurable business impact through AI and machine learning innovation
  • Experience leading cross-functional initiatives across multiple organizations and stakeholder groups
  • Ability to influence executive stakeholders and drive strategic technical decisions across large organizations
  • Exceptional communication, leadership, strategic thinking, and mentoring skills
  • Strong programming skills in Go, Python, SQL, and modern machine learning ecosystems
  • Experience designing and deploying end-to-end ML solutions, including data acquisition, feature engineering, model development, evaluation, deployment, and monitoring
  • Strong knowledge of experimentation frameworks, online evaluation, A/B testing, causal inference, and model validation methodologies
  • Proficiency in Anomaly Detection, MITRE entities, Detection Engineering,Triage and Investigation
  • Experience with modern AI infrastructure, large-scale data processing, distributed systems, and production ML platforms
  • Ability to communicate data-driven insights, uncertainty, assumptions, and trade-offs to technical and non-technical audiences

Nice to have

  • modern machine learning ecosystems
  • MITRE entities
  • Detection Engineering
  • Triage and Investigation
  • modern AI infrastructure
  • large-scale data processing
  • distributed systems
  • production ML platforms

What the JD emphasized

  • 8+ years of experience building and scaling large-scale AI/ML, search, retrieval, ranking in the cybersecurity space
  • Deep expertise in semantic retrieval, vector search, ranking systems, recommendation systems, NLP/LLMs, RAG architectures, and agentic AI systems
  • Experience operating large-scale production systems with demanding latency, scalability, reliability, and cost requirements
  • Proven track record of delivering measurable business impact through AI and machine learning innovation

Other signals

  • AI-native platform
  • advanced AI systems
  • analyze and prioritize millions of security events per second
  • rapidly identify and respond to emerging threats
  • intelligent models for anomaly detection, event classification, ranking, correlation, and automated security reasoning
  • ownership of complex technical challenges
  • drive innovation across the AI stack
  • shape the next generation of AI-powered security operations
  • large-scale retrieval, ranking, vector search, RAG, and anomaly detection systems
  • LLMs, AI-powered discovery, personalization, and autonomous AI workflows
  • AI-driven reasoning, ranking and investigation capabilities
  • end-to-end AI/ML architecture
  • data pipelines, feature engineering, model development, deployment, monitoring, evaluation, and continuous improvement
  • scalable architecture patterns, engineering standards, experimentation frameworks, and operational best practices
  • foundational investments and technical direction across AI platforms, retrieval infrastructure, model-serving systems, and ML tooling
  • Balance model quality, customer experience, latency, scalability, reliability, security, and infrastructure cost
  • Define evaluation methodologies, experimentation strategies, and success metrics
  • partner closely with Product, Engineering, Security, Infrastructure, and Operations teams
  • deliver scalable AI solutions
  • Communicate technical trade-offs, recommendations, and results
  • Lead highly ambiguous, multi-quarter initiatives
  • Influence organization-wide technical strategy, investment priorities, and long-term AI roadmap decisions
  • Mentor junior scientists
  • 8+ years of experience building and scaling large-scale AI/ML, search, retrieval, ranking in the cybersecurity space
  • Deep expertise in semantic retrieval, vector search, ranking systems, recommendation systems, NLP/LLMs, RAG architectures, and agentic AI systems
  • Strong understanding of retrieval and ranking trade-offs, experimentation methodologies, model evaluation, and operational excellence
  • Experience operating large-scale production systems with demanding latency, scalability, reliability, and cost requirements
  • Proven track record of delivering measurable business impact through AI and machine learning innovation
  • Experience leading cross-functional initiatives
  • Ability to influence executive stakeholders
  • Strong programming skills in Go, Python, SQL
  • Experience designing and deploying end-to-end ML solutions
  • Strong knowledge of experimentation frameworks, online evaluation, A/B testing, causal inference, and model validation methodologies
  • Proficiency in Anomaly Detection, MITRE entities, Detection Engineering, Triage and Investigation
  • Experience with modern AI infrastructure, large-scale data processing, distributed systems, and production ML platforms
  • Ability to communicate data-driven insights, uncertainty, assumptions, and trade-offs