Sr. Data Scientist (Remote)

CrowdStrike; Canada; Hybrid; CAD 180,000 - 236,000; Full time

Job summary

CrowdStrike is seeking a Senior Data Scientist to design, build and deploy AI systems that prioritize millions of security events per second. You will own end-to-end AI/ML architecture, from data pipelines to model deployment, while driving innovation across retrieval and anomaly detection at enterprise scale.

You will lead cross-functional teams, balance performance and cost, and shape the next generation of AI-powered security operations across the NGSIEM Agentic AI platform.

Qualifications

• Advanced degree or equivalent industry experience in ML/AI.
• Experience designing and deploying AI/ML systems at scale.
• Proven ability to lead cross-functional teams and manage complex projects.

Responsibilities

• Lead architecture for large-scale retrieval, ranking, vector search, RAG, and anomaly detection.
• Develop AI/ML models for anomaly detection, event classification, and security reasoning.
• Collaborate with Product, Engineering, Security, and Operations to deliver scalable AI capabilities.

Skills

AI/ML architecture

Retrieval systems

Vector search

Large-scale systems

Leadership

Cross-functional collaboration

Python

ML tooling

Education

Master's degree in CS/ML

Tools

Python

TensorFlow/PyTorch

LLM tooling

Job description

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Full time

R29023

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 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.

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.

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