Data Science Manager
About the role
🛠️ About our Engineering Teams
🧠 Your day-to-day
🧩 What you’ll be working on
- Set and align priorities with stakeholders across Autonomy, maintaining provisional three-, six-, and 12-month roadmaps that balance customer demand with team capacity.
- Work with technical leads and senior engineers to review technical proposals and designs, maintaining a high bar for statistical rigour and evaluation fidelity.
- Monitor delivery status and cadence, surface schedule risks early, and manage trade-offs with customers.
- Grow the team by hiring and onboarding data scientists, while investing in tooling and automation that enable the team to scale beyond headcount alone.
- Guide career-growth conversations, matching business needs with development opportunities and building progression pathways.
- Build cross-functional relationships that keep the team close to its customers and anticipate where support will be needed.
🙌 You should apply if
- You have three or more years' experience managing a team of five or more individual contributors.
- You have a track record of growing and maintaining high-performing teams.
- You have a strong data science foundation, including experience applying causal-inference methods in experimental or observational settings.
- You have built strong working relationships with cross-functional stakeholders and customers, translating their needs into clear team priorities.
- You have experience setting technical direction and reviewing designs and proposals from senior engineers.
- You are comfortable planning and communicating roadmaps, and managing delivery and expectations with demanding customers.
- You are comfortable working asynchronously across time zones with cross-functional partners.
- You are deeply curious about building something new and excited to help define AV2.0 and how Wayve builds it.
It would also be great if you have experience building or scaling an applied or embedded data science function; simulation, offline evaluation, or measurement for machine-learning systems; practical machine-learning experience, such as PyTorch; or taking research ideas into production. Experience with statistical rigour and experimental best practice, large datasets and distributed computing such as Spark or Hadoop, or fast-moving technology companies and startups is also valuable.
🌱 Not ticking every box? That's totally okay! If you're passionate about autonomy and keen to learn, we encourage you to apply even if you don't meet every requirement.
More about Wayve
How we work 💻- Locations & Flexible Working
🔍 The Interview Process
Initial call / recruiter screen
Competency interviews
Deep-dive interviews
Final interview
What’s in it for you
Not included in the source posting: qualifications, benefits.
Skills
Who can apply
The employer didn't state any visa, work authorization, citizenship or clearance requirements in this posting. Confirm with the employer before applying.
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