Manager, Data Science (remote, Esp)

CrowdStrike CrowdStrike · Enterprise · Spain · Remote

Manager, Data Science role focused on leading research strategy, technical vision, and team mentorship for next-generation AI assistants powered by LLMs in the cybersecurity space. The role involves driving innovation in LLM applications, making strategic decisions on model architectures, training, and deployment, and establishing best practices and evaluation frameworks.

What you'd actually do

  1. Lead and architect the research strategy for new GenAI agents/LLMs, setting the technical direction for the team
  2. Recruit, lead and mentor a team of top-tier data scientists engaged in professional fields, like ML and LLMs
  3. Drive innovation in LLM applications, including novel approaches to reasoning, summarisation, and interactivity
  4. Make strategic decisions about GenAI model architectures, training approaches, and deployment strategies
  5. Lead cross-functional initiatives and collaborate with senior leadership to align technical strategy with business goals

Skills

Required

  • Advanced degree (PhD or Masters) in Computer Science, Data Science, or a related field
  • 8+ years of applied machine learning / research experience
  • Proven track record of leading Data Science teams
  • Deep expertise in LLM training / deployment at scale
  • 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

Nice to have

  • Patents or significant intellectual property contributions in AI
  • 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
  • History of contributions to open-source ML projects

What the JD emphasized

  • production-grade models
  • leading Data Science teams
  • LLM training / deployment at scale
  • technical leadership experience
  • solving complex technical challenges at scale

Other signals

  • AI assistants powered by LLMs
  • GenAI agents/LLMs
  • LLM applications
  • GenAI model architectures, training approaches, and deployment strategies