Manager, Data Science (AI)

Location: Remote in the United Kingdom, Ireland, or Spain

Company

Cybersecurity company developing an AI-native platform for threat detection, security operations, and protection against breaches.

What you will do

• Lead, mentor, and develop a team of data scientists, including technical guidance, career development, and performance management.
• Set technical standards and best practices for machine learning development, deployment, monitoring, and production infrastructure.
• Define and execute machine learning strategy for threat detection and agentic AI security systems.
• Lead ML projects from research through production deployment, balancing innovation with measurable delivery.
• Collaborate with security research, engineering, product, and security domain experts to identify high-impact applications of ML.
• Guide advanced work on malware detection, behavioural threat analysis, security automation, publications, patents, and community contributions.

Requirements

• Master’s or PhD in Computer Science, Data Science, Mathematics, Physics, or a related STEM field, or a bachelor’s degree with equivalent experience.
• At least 5 years of data science and machine learning experience, including 2 or more years in technical leadership or team lead roles.
• Experience leading ML projects from research to production deployment and mentoring data scientists or ML engineers.
• Strong understanding of cybersecurity concepts, the threat landscape, and security operations.
• Programming proficiency in Python and experience with ML frameworks and big data technologies.
• Ability to collaborate across functions and explain complex technical concepts to non-technical stakeholders.

Nice to have

• Expertise in threat intelligence, malware analysis, or security operations.
• Experience with agentic AI systems, LLMs, autonomous security automation, or large sparse datasets.
• Knowledge of semi-supervised learning, online learning, model optimization, ML operations, A/B testing, and production ML infrastructure.
• Experience with AWS, Linux, hiring and scaling data science teams, or setting technical vision.
• Published research, patents, or contributions to ML or security communities.

Culture & Benefits

• Flexible work environment with autonomy and a focus on responsible AI adoption, experimentation, and innovation.
• Competitive compensation and equity awards.
• Physical and mental wellness programs, competitive vacation, and holidays.
• Paid parental and adoption leave.
• Professional development opportunities, employee networks, geographic groups, and volunteer opportunities.