Except for your knowledge of Data Science fundamentals, interviewers often ask about recent trends and problems the industry is working on. So, if you are looking for the trending topics asked in Data Science interviews in 2025, this article is for you. In this article, I’ll take you through the trending topics you should know about for your Data Science job interviews in 2025.
Trending Topics for Data Science Interviews
Below are some trending topics you should know about for your Data Science job interviews in 2025 and the type of questions you can face.
The Rise of Large Language Models (LLMs) & Generative AI
Large Language Models (LLMs) and generative AI have taken the world by storm with applications in chatbots, content creation, and business automation. However, despite their potential, these models present several challenges.
Interviewers will ask questions to test your knowledge of fine-tuning LLMs, retrieval-augmented generation (RAG), and techniques to enhance reliability. You might face questions such as:
- How do you fine-tune an LLM on domain-specific data?
- What are the benefits of retrieval-augmented generation (RAG) in LLMs?
- What are the trade-offs between using an API-based LLM and training a custom model?
Below are some resources to learn everything about Generative AI & LLMs:
AI-driven Automation & Agentic AI
As businesses strive to reduce human intervention in repetitive tasks, AI-driven automation has become a major focus area. Autonomous AI agents are being developed to handle data processing, customer service, and decision-making processes.
Interviewers will ask questions to test your knowledge about challenges in automation such as ensuring robustness, handling multi-step reasoning, and reducing reliance on human oversight. Interviewers may ask questions like:
- What is an AI agent, and how does it differ from a traditional ML model?
- How do reinforcement learning and LLMs work together in AI agents?
- How would you design an AI agent that autonomously processes financial data?
Below are some resources to learn everything about AI-driven Automation & Agentic AI:
Scalability & Deployment of Machine Learning Models
One of the biggest obstacles for organizations deploying AI solutions is ensuring that models operate efficiently at scale. Businesses require machine learning models that are cost-effective, scalable, and capable of running in real-time environments.
Interviewers will ask questions to test your understanding of model quantization, inference optimization, and versioning strategies. Expect questions such as:
- How do you optimize an ML model for inference on edge devices?
- What are the benefits of model quantization in deployment?
- What are the trade-offs between deploying a model as an API vs. embedding it in a microservice?
Below are some resources to learn about the deployment of Machine Learning Models:
The Need for Responsible & Explainable AI
With AI regulations such as the EU AI Act and GDPR coming into effect, there is a growing demand for transparent and explainable AI systems. Companies must ensure that AI models are not only accurate but also fair and interpretable.
Companies look for data professionals who can design AI systems that comply with ethical standards. You may face questions like:
- What techniques can make deep learning models explainable?
- How do you detect and mitigate bias in an AI system?
- What are the trade-offs between accuracy and fairness in AI models?
Below are some resources to learn about Explainable AI:
Summary
So, here are some trending topics you should know about for your Data Science job interviews in 2025:
- The Rise of Large Language Models (LLMs) & Generative AI
- AI-driven Automation & Agentic AI
- Scalability & Deployment of Machine Learning Models
- The Need for Responsible & Explainable AI
I hope you liked this article on the trending topics you should know about for your Data Science job interviews in 2025. Feel free to ask valuable questions in the comments section below. You can follow me on Instagram for many more resources.
