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B

Battery Smart

Data Science Intern

Interview Date

Summer 2025

Result

Selected

Difficulty

Moderate (Online Assessment), Medium (Technical Ro

Rounds

3 rounds

Drive Type

On-Campus (Internship)

Topics asked

Probability and StatisticsData AnalysisAptitudeSQLLSTM (architecturemathematical foundationbasic implementation)past projects and internships.

Detailed experience

Role: Data Science Intern

College: IIT Kharagpur

Interview Date: Summer 2025

Interview Type: On-Campus (Internship)

Result: Selected

Difficulty: Moderate (Online Assessment), Medium (Technical Round)

Rounds: 3 rounds

Topics Asked: Probability and Statistics, Data Analysis, Aptitude, SQL, LSTM (architecture, mathematical foundation, basic implementation), past projects and internships.

Experience:

The selection process for the Data Science Intern role at Battery Smart began with an online assessment. This assessment included questions on probability and statistics, data analysis, and aptitude. The probability and statistics questions were noted to be similar to problems found in "Heard on the Street" and "Brainstellar," with a recommendation to brush up on IIT KGP's Probability and Statistics course concepts. The data analysis section involved interpreting values from graphs and charts, requiring quick calculation skills. Aptitude-based questions were standard, akin to those in CAT competitive exams. The overall difficulty of the assessment was moderate, but required fast calculation due to time constraints.

Following the online assessment, offline interviews were conducted, consisting of two further rounds: a Group Discussion (GD) and a Technical Round. Out of 60 students selected for the GD, only 15 advanced to the Technical Round.

In the Technical Round, the candidate was asked a medium-level SQL query. This was followed by in-depth questions about their past projects and internships. Specifically, the interviewer delved into LSTM (Long Short-Term Memory), asking about its architecture, the mathematical foundation behind the model, and requiring a basic implementation of it.

The candidate's CV, with an emphasis on CGPA, was also a crucial part of the selection process. Tips included preparing the CV well, having prior internships and projects in Data Science or AI/ML, and being knowledgeable about every point listed on the CV. Mock interviews were also suggested to reduce nervousness.

Submitted anonymously12 NOVEMBER 2025