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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Sr. Data Scientist (Remote) - **Company:** CrowdStrike - **Location:** Wyoming, IL, United States (Remote available) - **Experience:** Expert - **Salary:** $140,000.0 - $215,000.0 - **Contract:** Permanent contract - **Skills:** A/B Testing, Artificial Intelligence, Amazon S3, Data Analysis, Automated Storage and Retrieval Systems, Big Data, Cyber Security, Computer Programming, Distributed Systems, Graph Database, Monitoring of Systems, Intrusion Detection and Prevention, Python (Programming Language), Machine Learning, Recommender Systems, Azure Machine Learning, Search Technologies, SQL Databases, Reinforcement Learning, Parquet, Feature Engineering, Large Language Models, Multi-Agent Systems, Apache Spark, Model Validation, Build Management, AI Platforms, Kubernetes, Information Technology, Low Latency, Apache Kafka, Free and Open-Source Software, Machine Learning Operations, Virtual Agents, Data Pipelines, Automation Anywhere, Golang - **Published:** September 3, 2026 - **Apply:** https://dejobs.org/x/x/0B03E3FAF4F54830A4CFDCFEB95C64F7/job/ ## About the Role insights, and solve complex problems. 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., * 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, 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, * 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. ## Description 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 proud to work for a mission-driven company leveraging AI to transform the way we work. CrowdStrikers drive their careers through flexibility and autonomy while also being expected to contribute to a culture of responsible AI adoption, experimentation, and innovation. We use an AI-first mindset as a force multiplier to proactively and continuously accelerate execution, build expertise, uncover, 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. 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. ## Related Videos - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Parquet, Delta, Iceberg & Ducklake - An introduction for developers](https://www.wearedevelopers.com/videos/100075-parquet-delta-iceberg-ducklake-an-introduction-for-developers) - [Go with the Flow: Stop the Leaks Before Your Memory's a Waterfall!](https://www.wearedevelopers.com/videos/100073-go-with-the-flow-stop-the-leaks-before-your-memory-s-a-waterfall) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data) - [OLAP for AI Applications and why you should care](https://www.wearedevelopers.com/videos/100212-olap-for-ai-applications-and-why-you-should-care) ## Related Articles - [Dev Digest 134 - Where pixels sing?](https://www.wearedevelopers.com/magazine/477-dev-digest-134-where-pixels-sing) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers) - [Dev Digest 121 - AI goes offline](https://www.wearedevelopers.com/magazine/456-dev-digest-121-ai-goes-offline) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Fully Remote Software Engineer Jobs](https://www.wearedevelopers.com/magazine/447-fully-remote-software-engineer-jobs)