Hi Fans.
I’m preparing for data science interviews and need advice. What technical questions are commonly asked? How should I handle case studies? What about behavioral questions—any tips? Are there industry-specific trends or questions I should know? Any general preparation tips or resources?
Thanks for any advice…
To prepare for a data science interview, research the company and its competitors, review the job requirements, and practice common questions. Understand different interview formats like phone, video, and in-person. Focus on technical skills like coding, statistics, and machine learning, and be ready to discuss data visualization and problem-solving techniques.
It’s not that horrible, really. Contained end-to-end machine learning analysis can be nearly enjoyable; kaggles isn’t that complicated. Only 5% of data science is actually data science, so it’s critical to get it right. The majority of data science (DS) is actually data engineering, API development, containerization, service management, etc. For me, handling lambdas on my own for AWS has been a headache. Not because DE is incredibly hard by magic, but rather because I’m not very good at it and I need to practice.
Regarding comprehension of business cases and communication, they are only human abilities that are typically pre-installed. It is remedial, but it does happen if you need to pick it up.
Unfortunately, you are only covering roughly 25% of the necessary surface area.
Focus on statistics, machine learning, data munging, SQL, coding, and data visualization. Practice problem-solving, communication, and teamwork skills. Stay updated on industry trends and build a strong portfolio.