NPCI

Role: SDE-I

College: IIT-Bombay

Interview Date: Offer in September 2023 (Interview experience posted December 30, 2023)

Interview Type: On-Campus (Campus Placements)

Result: Selected (Offer received 5 minutes post-interview)

Difficulty: Medium to Hard (DSA), Easy (Interview for basics)

Rounds: 2 rounds

Topics Asked: English Comprehension, Quantitative Aptitude, DILR, Machine Learning, Deep Learning, Essay Writing, DSA (Dynamic Programming, Binary Trees), HR, Pointers, Call by Value/Reference, OOPS (Pillars, Polymorphism), Java Basics, SQL (Joins), Web Hosting, Data Science Projects, Scaling Products, Machine Learning Models (LSTM, RNN, Deep Learning).

Experience:

The recruitment process was for SDE-I at NPCI during campus placements.

Round 1: Online Assessment (OA)
The OA consisted of four parts:

• English Comprehension (20 questions).
• Quantitative Aptitude (20 medium-level problems).
• DILR (20 questions).
• Machine Learning and Deep Learning MCQs (30 questions, 20 minutes).
• Essay Writing on a topic like "HealthCare Facilities in India" (around 250 words).
• Two DSA questions. Examples mentioned: "Path finding in a grid problem using Dynamic Programming (Medium - Hard level)" and "Recover Binary Tree". Questions were different for everyone.

Round 2: Online Interview
This was a single online round with a panel of 5 members from SDE, Machine Learning, Data Analytics, Blockchain, and HR.

• HR Questions: Started with a basic introduction and common HR questions like "Why NPCI and who are its competitors?".
• Technical Questions (SDE): Types of pointers, call by value and call by reference, pillars of OOPS, different types of polymorphism, basics of Java, SQL queries (joins and different types of joins), core concepts of web hosting, and problems faced in web hosting.
• Technical Questions (Data/ML): Discussion on all projects and internships related to Machine Learning mentioned in the resume, analysis of problems faced while scaling a product, case-based designing of Machine Learning models, questions on LSTM, RNN, and other Deep Learning models.

The interview lasted around 70-75 minutes, and the candidate received an offer just 5 minutes after the interview. The overall recruitment process was described as innovative and soft.