Lead Data Scientist

Overview

Lead Data Scientist at Faculty drives strategic ML direction and high-impact, production-grade solutions within a regulated financial services context. You lead cross-functional teams, shape technical standards, and manage customer relationships to translate complex problems into reliable, scalable AI outcomes. This role blends deep ML expertise with commercial focus, enabling innovative solutions that meet business goals. You will mentor peers and influence organisational technical excellence while partnering with clients to achieve long-term success.

Responsibilities

• Set technical direction for complex, business-critical projects balancing speed, innovation, and reliability
• Design and implement production-grade AI solutions with clear architecture documentation
• Define project problems, create roadmaps, and oversee end-to-end delivery across multi-disciplinary teams
• Lead scoping and feasibility studies for high-value sales opportunities and strategic client engagements
• Manage client relationships and align technical solutions with long-term commercial goals
• Drive adoption of best practices and robust technical processes across the Data Science craft
• Mentor and develop other data scientists and contribute to technical excellence of the organisation

Key requirements

• Depth of expertise in at least one ML domain
• Strong technical breadth across the data science landscape
• Skilled technical leader with mentoring and people management experience
• Proven project management abilities with capability to split complex problems into actionable work streams
• Track record delivering innovative outcomes under commercial pressure
• Strong customer leadership and ability to establish trusted advisor relationships
• Cross-functional collaboration with Engineering, Commercial, and Infrastructure teams
• Experience extending technical oversight to business unit-level initiatives
• Comfort working in a regulated environment with high-stakes projects

• leadership
• mentoring
• communication with demanding clients
• machine learning domain expertise
• production-grade system design
• technical strategy and roadmapping

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