Senior Data ScientistCrowdStrike is seeking an exceptional Senior Data Scientist to join our NGSIEM Agentic AI team. In this role, you will design, build and deploy advanced AI systems that analyze and prioritize millions of security events per second, enabling organizations to rapidly identify and respond to emerging threats. You will develop intelligent models for anomaly detection, event classification, ranking, correlation, and automated security reasoning.
As a key contributor, you will take ownership of complex technical challenges, drive innovation across the AI stack, and help shape the next generation of AI-powered security operations.This is a hybrid role based out of our office in Sunnyvale, CA, requiring 2 days per week on-site.AI, Search & Retrieval StrategyLead the architecture and technical strategy for large-scale retrieval, ranking, vector search, RAG, and anomaly detection systems operating at enterprise scale.Drive innovation across LLMs, AI-powered discovery, personalization, and autonomous AI workflows.Define the future direction of AI-driven reasoning, ranking and investigation capabilities across the platform.AI/ML Architecture & Technical LeadershipOwn end-to-end AI/ML architecture, including data pipelines, feature engineering, model development, deployment, monitoring, evaluation, and continuous improvement.Establish scalable architecture patterns, engineering standards, experimentation frameworks, and operational best practices across multiple teams.Drive 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 when making architectural decisions.Product & Business ImpactDefine evaluation methodologies, experimentation strategies, and success metrics to assess product, model, and business impact.Partner closely with Product, Engineering, Security, Infrastructure, and Operations teams to identify high-value opportunities and deliver scalable AI solutions.Communicate technical trade-offs, recommendations, and results clearly to both technical and executive audiences.Technical LeadershipLead highly ambiguous, multi-quarter initiatives spanning Product, Engineering, Data Science, and other stakeholders.Influence organization-wide technical strategy, investment priorities, and long-term AI roadmap decisions.Represent the organization in executive reviews and drive alignment on major technical and product initiatives.Mentor junior scientists while fostering a culture of technical excellence and innovation.What You'll Need: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.Proven experience utilizing AI technologies to enhance decision-making, streamline workflows and processes, improve efficiency and drive business outcomes.Technologies:Python, Go, SQL, Spark, Kafka, S3, Iceberg, ParquetMachine Learning, Deep/Reinforcement Learning, Time-Series Modeling, Anomaly Detection, Recommendation Systems, Ranking SystemsLLMs, RAG, Agentic AI, Multi-Agent Systems, AI EvaluationVector Search, Hybrid Search, Embeddings, Retrieval Systems, Knowledge Graphs, Ranking & Relevance OptimizationKubernetes, Distributed Systems, Model Serving, Feature Stores, ML Pipelines, Experimentation Platforms, Model MonitoringThreat Detection, Security Analytics, UEBA, Detection Engineering, AI-Powered SOC WorkflowsBonus Points:Published research, patents, open-source contributions, or recognized thought leadership in AI, machine learning, search, retrieval, or cybersecurity.Experience building large-scale search, recommendation, retrieval, or agentic AI systems serving enterprise or consumer products.Experience leading technical strategy for AI platforms, ML infrastructure, or AI-native product initiatives.Demonstrated success driving zero-to-one innovation and scaling solutions to enterprise-wide adoption.