Sr. Manager, Data Science (Remote - UK, Spain or Romania)

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. 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 a Manager, Applied Research to join our team building greenfield next-generation AI that stops breaches and is powered by large language models (LLMs), deep learning, and other modern AI techniques. You will both manage and help implement innovative systems and work closely with other scientists and software engineers to provide mentorship, technical leadership, and strategic direction.

You will shape the technical vision by bringing leading edge AI technology into our product, contribute to production systems, and make high-impact decisions that influence the company's AI strategy. This is a unique opportunity to lead groundbreaking developments in cybersecurity AI that will help keep our customers safe. This opportunity presents a dynamic, growth-oriented startup environment for a driven, research-focused professional.

What You’ll Do:

• Lead and architect the research strategy for applying AI to cybersecurity.

• Recruit, lead and mentor a team of top-tier data scientists engaged in professional fields, like ML and LLMs

• Drive innovation in AI applications, including novel approaches to reasoning, summarisation, and interactivity

• Contribute code from proof-of-concept to production ready systems that perform at CrowdStrike’s massive scale.

• Make strategic decisions about GenAI and deep learning model architectures, training approaches, and deployment strategies

• Lead cross-functional initiatives and collaborate with senior leadership to align technical strategy with business goals

• Represent CrowdStrike's technical excellence through publications, speaking engagements, and thought leadership

• Establish best practices, technical standards, and evaluation frameworks for the team

What You’ll Need:

• Advanced degree (PhD or Masters) in Computer Science, Data Science, or a related field

• 8+ years of applied machine learning / research experience, with demonstrated leadership in developing production-grade models

• Proven track record of leading Data Science teams

• Deep expertise in LLM and deep learning training, fine tuning, and deployment at scale.

• Have a bias-for-action, ability to make high-judgement decisions, and be comfortable in the face of ambiguity.

• Strong technical leadership experience, including mentoring teams and driving technical strategy

• Advanced knowledge of Python, Deep Learning frameworks, and cloud technologies

• Expert-level understanding of GPU technologies and optimisation techniques

• Outstanding communication skills with ability to influence senior stakeholders

• Track record of solving complex technical challenges at scale

Bonus Points:

• Strong research portfolio with publications in leading AI journals and conferences

• Experience with cybersecurity applications of machine learning

• Track record of successful research-to-production implementations at scale

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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 opportun