Data Science Manager (Autonomous Driving)

Location: London, United Kingdom; hybrid working with two days per week in the office

Company

hirify.global is building an end-to-end AI platform for autonomous driving that learns from real-world experience and supports scalable vehicle deployment.

What you will do

• Lead the Applied Methods Data Science team supporting the Autonomy organisation.
• Set priorities and maintain three-, six-, and 12-month roadmaps with cross-functional stakeholders.
• Review technical proposals and designs with technical leads and senior engineers, maintaining statistical rigour and evaluation fidelity.
• Monitor delivery, identify schedule risks, and manage customer-facing trade-offs.
• Hire, onboard, and develop data scientists while investing in tooling and automation.
• Build relationships with customers and engineering partners to anticipate future support needs.

Requirements

• At least three years of experience managing a team of five or more individual contributors.
• Experience building and maintaining high-performing teams.
• Strong data science foundation, including causal-inference methods in experimental or observational settings.
• Experience setting technical direction, reviewing designs, and translating stakeholder needs into team priorities.
• Experience planning roadmaps, managing delivery, and working asynchronously across time zones.
• Curiosity about autonomous mobility and defining the future of AV technology.

Nice to have

• Experience scaling an applied or embedded data science function.
• Experience with simulation, offline evaluation, measurement for machine-learning systems, or taking research into production.
• Practical machine-learning experience such as PyTorch, and experience with large datasets or distributed computing such as Spark or Hadoop.
• Experience in fast-moving technology companies or startups.

Culture & Benefits

• Hybrid working with core hours and access to vehicle workshops and labs.
• Relocation support and visa sponsorship where applicable.
• Meaningful equity and annually benchmarked salaries.
• Learning and development budgets for training, conferences, and professional growth.
• Health insurance, dental coverage, enhanced parental leave, pension or retirement benefits, therapy access, wellbeing partnerships, and team socials.

Hiring process

• Recruiter screen followed by manager, quantitative-domain, and code-review interviews.
• Deep-dive interviews covering cross-functional collaboration, leadership and management, and causal inference.
• Final interview with the leadership team.