Interview Experience for a Data Position at Digikala During my interview for a data position at Digikala, one of the questions I was asked was about Object-Oriented Programming (OOP) and its core concepts. At first, this seemed unrelated to the role, but upon deeper reflection, I realized its significance. Even in data science and analytics, writing maintainable and modular code is essential, especially when working with large-scale systems and real-world applications. Understanding OOP principles (like encapsulation, inheritance, polymorphism, and abstraction) helps in structuring code that is scalable, reusable, and closer to production-level standards. For anyone preparing for a data-related role at Digikala (or similar companies), I’d recommend brushing up on OOP concepts and their practical applications in Python. It’s not just about writing scripts—it’s about building systems that work efficiently in a team-based, production environment.