Wipro
Global information technology, consulting and business process services company.
4 Rounds
~21 Days
Medium
The Interview Loop
Recruiter Screen (30 min)
Standard fit check, behavioral questions, and resume overview.
Technical Loop (3-4 Rounds)
Deep dive into domain knowledge, coding, and system design.
Interview Question Bank
Data Scientist
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Behavioral
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medium
Tell me about a time you had to explain a complex machine learning model's predictions to a non-technical client stakeholder.
#Stakeholder Management
#Model Interpretability
#Soft Skills
Data Scientist
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Behavioral
•
medium
Describe a situation where a client changed the project requirements halfway through the development cycle. How did you handle it?
#Agile
#Client Management
#Problem Solving
Data Scientist
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Behavioral
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hard
Tell me about a time a machine learning model you deployed failed or performed poorly in production. What was the root cause and how did you fix it?
#Production Failures
#Debugging
#Accountability
Data Scientist
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Behavioral
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easy
Working at an IT services company like Wipro often means juggling multiple client deliverables. How do you prioritize your tasks?
#Prioritization
#Consulting
#Organization
Data Scientist
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Behavioral
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easy
Why do you want to work as a Data Scientist at Wipro specifically, compared to a product-based company?
#Motivation
#Company Knowledge
#Career Goals
Data Scientist
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Coding
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medium
Write a SQL query using window functions to find the second highest salary in each department for a client's HR database.
#Window Functions
#Data Aggregation
#SQL
Data Scientist
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Coding
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medium
Given a large dataset of customer transactions, write a Pandas script to calculate the month-over-month churn rate.
#Python
#Pandas
#Time Series Analysis
Data Scientist
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Coding
•
easy
Write a Python function from scratch to calculate the cosine similarity between two lists of numbers.
#Python
#Math
#Vector Operations
Data Scientist
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Coding
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hard
Write a PySpark script to join a 10GB customer table with a 500MB transaction table. How would you optimize this join?
#PySpark
#Distributed Computing
#Optimization
Data Scientist
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Coding
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hard
Write a SQL query to identify the top 3 most frequently purchased pairs of products (Market Basket Analysis prep).
#Self Joins
#Aggregations
#Data Mining
Data Scientist
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Coding
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hard
Write a Python script using Pandas to find the top 5 customers who have the highest continuous streak of daily purchases.
#Python
#Pandas
#Gaps and Islands
Data Scientist
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Coding
•
medium
Write a SQL query to calculate the 7-day rolling average of daily revenue for a retail client.
#Window Functions
#Time Series
#SQL
Data Scientist
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System Design
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hard
Design a scalable product recommendation system for a large e-commerce client. Walk me through the data pipeline, model choice, and serving infrastructure.
#Recommendation Systems
#Scalability
#Architecture
Data Scientist
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System Design
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medium
How would you design a system to monitor a deployed machine learning model for data drift and concept drift?
#Model Monitoring
#Data Drift
#MLOps
Data Scientist
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System Design
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hard
Design a predictive maintenance system for a manufacturing client using streaming IoT sensor data.
#IoT
#Streaming Data
#Predictive Maintenance
Data Scientist
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System Design
•
medium
Walk me through the end-to-end lifecycle of deploying a machine learning model using AWS SageMaker or Azure Machine Learning.
#Cloud Platforms
#Deployment
#CI/CD
Data Scientist
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System Design
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hard
Design an automated document extraction pipeline using OCR and LLMs for a banking client processing thousands of loan applications daily.
#OCR
#LLMs
#Pipeline Design
Data Scientist
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System Design
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hard
Design an architecture for a real-time credit card fraud detection system. The client requires sub-50 millisecond latency.
#Real-time Processing
#Low Latency
#Fraud Detection
Data Scientist
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Technical
•
medium
Explain the difference between Bagging and Boosting. How does the XGBoost algorithm work under the hood?
#Ensemble Methods
#XGBoost
#Decision Trees
Data Scientist
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Technical
•
medium
You are building a fraud detection model for a banking client where the fraud cases are less than 0.1% of the data. How do you handle this extreme class imbalance?
#Imbalanced Data
#SMOTE
#Evaluation Metrics
Data Scientist
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Technical
•
easy
Explain the Bias-Variance Tradeoff. How do you diagnose if a model deployed for a client is overfitting?
#Model Evaluation
#Overfitting
#Statistics
Data Scientist
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Technical
•
medium
What are the core assumptions of Linear Regression? What happens to your model if the assumption of homoscedasticity is violated?
#Linear Regression
#Statistical Assumptions
#Econometrics
Data Scientist
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Technical
•
medium
How does a Random Forest model calculate feature importance?
#Random Forest
#Feature Engineering
#Interpretability
Data Scientist
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Technical
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hard
Explain the mathematical intuition behind Logistic Regression. Why do we use Log-Loss instead of Mean Squared Error (MSE) as the cost function?
#Logistic Regression
#Loss Functions
#Optimization
Data Scientist
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Technical
•
medium
What is the difference between L1 (Lasso) and L2 (Ridge) regularization? In what client scenario would you prefer L1 over L2?
#Regularization
#Feature Selection
#Linear Models
Data Scientist
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Technical
•
easy
Explain the working of the K-Means clustering algorithm. How do you determine the optimal number of clusters (K)?
#Unsupervised Learning
#Clustering
#K-Means
Data Scientist
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Technical
•
medium
How do you handle categorical variables with extremely high cardinality (e.g., zip codes) in a machine learning model?
#Feature Engineering
#Categorical Encoding
Data Scientist
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Technical
•
hard
Explain the architecture of a Transformer model. How does the Self-Attention mechanism work?
#NLP
#Transformers
#Attention Mechanism
Data Scientist
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Technical
•
hard
What is RAG (Retrieval-Augmented Generation)? How would you design a RAG pipeline for a Wipro enterprise client to query their internal HR documents?
#LLMs
#RAG
#Vector Databases
Data Scientist
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Technical
•
medium
How do you deal with the vanishing gradient problem in deep neural networks?
#Neural Networks
#Optimization
#Activation Functions
Data Scientist
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Technical
•
medium
A client wants to forecast weekly sales for the next 6 months. Compare ARIMA and LSTM for this task. Which would you choose and why?
#Forecasting
#ARIMA
#LSTM
Data Scientist
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Technical
•
medium
Explain the concept of A/B testing. How do you calculate the required sample size before launching an A/B test for a new website feature?
#A/B Testing
#Hypothesis Testing
#Experimentation
Data Scientist
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Technical
•
medium
What are the differences between BERT and GPT architectures? When would you use one over the other?
#NLP
#BERT
#GPT
Data Scientist
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Technical
•
hard
How do you optimize a PySpark job that is failing due to OutOfMemory (OOM) errors on the executor nodes?
#PySpark
#Memory Management
#Debugging
Data Scientist
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Technical
•
medium
Explain the concept of Data Leakage in machine learning. Give an example of how it might occur in a client's churn prediction model.
#Data Leakage
#Model Validation
#Feature Engineering
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