Define and implement statistical testing frameworks for AI evaluation. Design bias and fairness methodologies across AI systems. Build robust, defensible methodologies for high-stakes environments.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
Job Description
Do you want to define how AI systems are trusted, not just built?
Have you ever had to defend your analysis in high-stakes or regulated environments?
Are you ready to shape the standards for AI fairness and evaluation from the ground up?
A venture-backed AI start-up is building the trust layer for modern AI systems, auditing models for bias, fairness, and compliance. With strong early traction and a growing US customer base, they are positioning themselves at the centre of AI regulation and enterprise adoption. The team is small, high-calibre, and working directly with customers on high-impact, real-world problems.
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This role is a foundational Senior Data Scientist hire, focused on defining how AI systems are evaluated and validated. You will combine deep statistical expertise with product thinking to build robust, defensible methodologies used in high-stakes environments.
Key responsibilities
• Define and implement statistical testing frameworks for AI evaluation
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• Design bias and fairness methodologies across AI systems
• Build and validate synthetic datasets for testing scenarios
• Translate regulatory requirements into practical evaluation approaches
• Establish standards for analysis, interpretation, and defensibility
• Work closely with founders on product and strategic direction
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Key details
• Salary: £100k–£120k+ + equity
• Working model: Hybrid (3 days London office)
• Tech stack: Python, statistical modelling, AI evaluation methods
• Visa: Sponsorship available
Interested? Please apply below.
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