Sr. Data Scientist (Hybrid)

As a global leader in cybersecurity, CrowdStrike protects the people, processes and technologies that drive modern organizations. Since 2011, our mission hasn’t changed — we’re here to stop breaches, and we’ve redefined modern security with the world’s most advanced AI-native platform. We work on large scale distributed systems, processing almost 3 trillion events per day and this traffic is growing daily. Our customers span all industries, and they count on CrowdStrike to keep their businesses running, their communities safe and their lives moving forward. We’re also a mission-driven company. We cultivate a culture that gives every CrowdStriker both the flexibility and autonomy to own their careers. We’re always looking to add talented CrowdStrikers to the team who have limitless passion, a relentless focus on innovation and a fanatical commitment to our customers, our community and each other. Ready to join a mission that matters? The future of cybersecurity starts with you.

About the Role:
CrowdStrike 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.

What You'll Do:

AI, Search & Retrieval Strategy

• Lead 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 Leadership

• Own 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 Impact

• Define 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 Leadership

• Lead 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.

Technologies:

• Python, Go, SQL, Spark, Kafka, S3, Iceberg, Parquet

• Machine Learning, Deep/Reinforcement Learning, Time-Series Modeling, Anomaly Detection, Recommendation Systems, Ranking Systems

• LLMs, RAG, Agentic AI, Multi-Agent Systems, AI Evaluation

• Vector Search, Hybrid Search, Embeddings, Retrieval Systems, Knowledge Graphs, Ranking & Relevance Optimization

• Kubernetes, Distributed Systems, Model Serving, Feature Stores, ML Pipelines, Experimentation Platforms, Model Monitoring

• Threat Detection, Security Analytics, UEBA, Detection Engineering, AI-Powered SOC Workflows

Bonus 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.

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Benefits of Working at CrowdStrike:

• Market leader in compensation and equity awards

• Comprehensive physical and mental wellness programs

• Competitive vacation and holidays for recharge

• Paid parental and adoption leaves

• Professional development opportunities for all employees regardless of level or role

• Employee Networks, geographic neighborhood groups, and volunteer opportunities to build connections

• Vibrant office culture with world class amenities

• Great Place to Work Certified™ across the globe

CrowdStrike is proud to be an equal opportunity employer. We are committed to fostering a culture of belonging where everyone is valued for who they are and empowered to succeed. We support veterans and individuals with disabilities through our affirmative action program.

CrowdStrike is committed to providing equal employment opportunity for all employees and applicants for employment. The Company does not discriminate in employment opportunities or practices on the basis of race, color, creed, ethnicity, religion, sex (including pregnancy or pregnancy-related medical conditions), sexual orientation, gender identity, marital or family status, veteran status, age, national origin, ancestry, physical disability (including HIV and AIDS), mental disability, medical condition, genetic information, membership or activity in a local human rights commission, status with regard to public assistance, or any other characteristic protected by law. We base all employment decisions--including recruitment, selection, training, compensation, benefits, discipline, promotions, transfers, lay-offs, return from lay-off, terminations and social/recreational programs--on valid job requirements.

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