Bosch

Role: Internship (Data Science & Software Roles)

College: Not Specified

Interview Date: Late 2022 (Internship: July 2022 - January 2023)

Interview Type: On-Campus, Internship

Result: Selected

Difficulty: Easy (Coding questions)

Rounds: 3 rounds

Topics Asked: Aptitude, Coding, General Technical, Data Science (specific), Software Systems (specific), Resume Walkthrough, Projects, Current Technologies (e.g., Generative AI like ChatGPT), HR Questions

Experience:

Karthik Naren shared his six-month internship experience at Bosch, which took place from July 2022 to January 2023. The interview process for internship roles included three rounds.

Round 1: Technical Assessment

This round was 90 minutes long and was specific to the department. Data Science students had questions from data science, and software students from software. The assessment was divided into:

• 20 minutes for aptitude.
• 40 minutes for coding (2 questions, described as "pretty easy," sufficient time).
• 20 minutes for general technical questions.

The aptitude section had 20 questions, technical had 20, and coding had 2. The time for aptitude was considered very less.

Round 2: Technical Interview

This round lasted for approximately 40 minutes to an hour. Interviewers either asked candidates to walk through their resume or highlight differentiating points. They often jumped straight to project topics, asking for a deep understanding of the workflow and the candidate's role, especially for group projects. For Data Science roles, questions were focused on current technologies like "how ChatGPT works," rather than older topics like K-means or random forest, indicating an expectation for candidates to be updated on current trends.

Round 3: HR Round

From 2023 onwards, an HR round was made compulsory to assess the candidate's likelihood of joining Bosch and to discuss location preferences.

Tips for clearing the process included having a good understanding of one's field and general aptitude for the online assessment. For the technical interview, a deep understanding of projects and current technologies in the chosen field was crucial. For example, in Data Science, understanding the workflow of generative AI was expected.