I was recently invited to interview for a Data Scientist position in the Risk Management team at the London office. The interview was disappointing and did not reflect the role as described in earlier stages. The Data Science Manager skipped any meaningful discussion about the actual work, team dynamics, or strategic challenges they face. Instead, the interview consisted almost entirely of textbook definitions and technical minutiae that had little relevance to the day-to-day responsibilities of the role. When I attempted to discuss practical applications or strategic approaches to risk management, these were quickly dismissed in favor of returning to narrow technical questions. There was an excessive focus on memorised definitions rather than problem-solving ability or real-world experience. For example, they spent significant time quizzing on specific algorithm parameters but showed no interest in discussing how these tools would be applied to actual business problems. The most concerning aspect was the lack of big-picture thinking. For a role advertised as needing to "translate business requirements into data science use cases," there was surprisingly little interest in discussing business context or stakeholder management. I discovered this position had been open for over 4 months, and after experiencing their interview process, I completely understand why. Their approach to interviewing suggests a disconnect between what they claim to need ie business-focused data scientists and what they're actually screening for textbook technical knowledge. The interview left me with serious concerns about the team's approach to data science and whether they truly understand what skills are needed for effective risk management in their industry.