Data Science Manager, Applied Methods for Autonomy

EngineersOfAI; Greater London; Hybrid; GBP 110,000 - 150,000; Full time

Job summary

Wayve in London seeks a Manager of our Applied Methods Data Science team to turn experimental and observational driving analyses into evals and actionable insights for engineering. You will lead a group of data scientists, align priorities with stakeholders, and scale the team through headcount and tooling.

The role requires a strong DS foundation, experience with causal inference, and a track record of building relationships with cross-functional partners.

Qualifications

• 3+ years experience managing a team of 5+ ICs
• Track record of growing and maintaining high-performing teams
• Strong data science foundation with causal inference methods
• Experience turning stakeholder needs into team priorities
• Experience setting technical direction and reviewing designs/proposals of engineers
• Roadmapping and delivery management for demanding customers

Responsibilities

• Set and align priorities with stakeholders across Autonomy and maintain 3/6/12 month roadmaps
• Review proposals and designs with technical leads and senior engineers
• Monitor status and cadence, surface slippage early, manage trade-offs with customers
• Grow the team: hire and onboard data scientists; invest in tooling/automation
• Guide career growth conversations and build progression paths
• Build cross-functional relationships with customers and internal partners

Skills

Team leadership

Data science

Causal inference

Stakeholder management

Technical direction

Roadmap planning

Cross-functional collaboration

AV2.0 vision

Tools

PyTorch

Simulation tooling

ML evaluation tooling

Job description

Wayve in London seeks a Manager of our Applied Methods Data Science team to turn experimental and observational driving analyses into evals and actionable insights for engineering. You will lead a group of data scientists, align priorities with stakeholders, and scale the team through headcount and tooling.

The role requires a strong DS foundation, experience with causal inference, and a track record of building relationships with cross-functional partners.