DXC Technology
American multinational B2B IT services provider.
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 highly technical machine learning concept to a non-technical client or business stakeholder.
#Stakeholder Management
#Communication
#Consulting
Data Scientist
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Behavioral
•
medium
Describe a time when a client had unrealistic expectations about what AI/ML could achieve for their legacy systems. How did you manage the situation?
#Client Management
#Conflict Resolution
#Expectation Management
Data Scientist
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Behavioral
•
medium
Tell me about a time you received a dataset from a client that was completely undocumented and messy. How did you proceed?
#Data Exploration
#Client Communication
#Ambiguity
Data Scientist
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Behavioral
•
medium
Tell me about a time a machine learning model you built failed or underperformed in production. What was the root cause and how did you fix it?
#Failure Analysis
#Continuous Improvement
#Accountability
Data Scientist
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Behavioral
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easy
Why do you want to work as a Data Scientist at DXC Technology specifically?
#Company Knowledge
#Motivation
#Career Goals
Data Scientist
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Behavioral
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easy
Describe a project where you had to collaborate closely with Data Engineers and DevOps/MLOps teams to deliver a solution.
#Teamwork
#Cross-functional Collaboration
#Agile
Data Scientist
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Coding
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medium
Write a SQL query to calculate the cumulative sum of revenue per month for the year 2023.
#SQL
#Window Functions
#Cumulative Sum
Data Scientist
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Coding
•
medium
Write a SQL query using window functions to calculate the 7-day rolling average of daily transaction volumes for a specific enterprise client.
#SQL
#Window Functions
#Data Aggregation
Data Scientist
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Coding
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easy
Write a Python script using Pandas to merge two large datasets (e.g., client CRM data and transaction logs), handle missing values, and group by a specific category to find the sum.
#Python
#Pandas
#Data Cleaning
Data Scientist
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Coding
•
medium
Write a Python function from scratch to calculate the TF-IDF scores for a given list of documents without using Scikit-Learn.
#Python
#NLP
#Math Implementation
Data Scientist
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Coding
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medium
Write a SQL query to find the top 3 highest-paid employees in each department. Handle ties appropriately.
#SQL
#Window Functions
#Ranking
Data Scientist
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Coding
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hard
Implement the K-Means clustering algorithm from scratch in Python. You do not need to optimize it, but the logic must be sound.
#Python
#Machine Learning Algorithms
#Math
Data Scientist
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Coding
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easy
Given an array of integers and a target sum, write a Python function to return the indices of the two numbers that add up to the target. (Two Sum)
#Python
#Hash Maps
#Time Complexity
Data Scientist
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Coding
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hard
Write a SQL query to find the retention rate of users. Specifically, find the percentage of users who logged in on day 1 and also logged in on day 2.
#SQL
#Self Joins
#Cohort Analysis
#Product Analytics
Data Scientist
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System Design
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hard
Design an end-to-end architecture for deploying a predictive maintenance model for a manufacturing client. How do you get data from IoT sensors to the model and return predictions?
#IoT
#MLOps
#Cloud Architecture
#Streaming
Data Scientist
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System Design
•
medium
How would you monitor a deployed machine learning model for concept drift and data drift? What steps would you take if drift is detected?
#Model Monitoring
#Concept Drift
#Data Drift
#Production ML
Data Scientist
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System Design
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hard
Design an NLP pipeline to extract key clauses and entities from thousands of scanned legacy PDF contracts for a legal client.
#NLP
#OCR
#Information Extraction
#LLMs
Data Scientist
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System Design
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medium
Design a system to automatically categorize and route incoming IT support tickets to the correct resolution team using machine learning.
#NLP
#Text Classification
#API Design
#Enterprise Architecture
Data Scientist
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System Design
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hard
Design a real-time anomaly detection system for network security logs. The system must process 100,000 events per second.
#Streaming
#Anomaly Detection
#Scalability
#Cybersecurity
Data Scientist
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System Design
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medium
If a client wants to migrate their on-premise machine learning workloads to the cloud, how would you evaluate whether to use AWS SageMaker vs Azure Machine Learning?
#Cloud Computing
#AWS
#Azure
#MLOps
Data Scientist
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Technical
•
medium
Explain the difference between Random Forest and Gradient Boosting. In what scenario would you choose one over the other for a client's predictive model?
#Ensemble Methods
#Random Forest
#XGBoost
#Model Selection
Data Scientist
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Technical
•
medium
We often work with clients in the financial sector. How would you handle a highly imbalanced dataset for a credit card fraud detection model?
#Imbalanced Data
#SMOTE
#Class Weights
#Fraud Detection
Data Scientist
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Technical
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easy
Explain the Bias-Variance tradeoff. How does regularizing a model affect its bias and variance?
#Model Evaluation
#Regularization
#Statistical Theory
Data Scientist
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Technical
•
medium
What is the mathematical difference between L1 (Lasso) and L2 (Ridge) regularization? When would you use L1 over L2?
#Regularization
#Linear Models
#Feature Selection
Data Scientist
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Technical
•
medium
Explain the concept of statistical power and p-values in the context of A/B testing a new feature on an enterprise web portal.
#A/B Testing
#Hypothesis Testing
#P-value
Data Scientist
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Technical
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hard
How do you scale a machine learning data preparation pipeline when the dataset is too large to fit into a single machine's RAM? Explain how you would use PySpark.
#PySpark
#Distributed Computing
#Big Data
Data Scientist
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Technical
•
easy
What are your strategies for handling missing data in a dataset provided by a client? How do you decide between imputation and dropping rows?
#Data Cleaning
#Imputation
#EDA
Data Scientist
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Technical
•
medium
Why can't you use standard k-fold cross-validation for time series forecasting? What should you use instead?
#Cross-Validation
#Time Series
#Model Evaluation
Data Scientist
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Technical
•
medium
When evaluating a binary classifier, when would you prefer the Precision-Recall curve over the ROC curve?
#ROC-AUC
#Precision-Recall
#Imbalanced Data
Data Scientist
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Technical
•
medium
What is multicollinearity in a regression model? How do you detect it, and how do you resolve it?
#Linear Regression
#VIF
#Feature Engineering
Data Scientist
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Technical
•
easy
What are the most effective techniques for detecting outliers in a multi-dimensional dataset?
#Outlier Detection
#Isolation Forest
#Z-score
Data Scientist
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Technical
•
hard
Explain the self-attention mechanism in Transformer models. Why has it largely replaced RNNs for NLP tasks?
#NLP
#Transformers
#Attention Mechanism
#LLMs
Data Scientist
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Technical
•
medium
Explain the kernel trick in Support Vector Machines (SVM). Name two common kernels and when you would use them.
#SVM
#Algorithms
#Math
Data Scientist
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Technical
•
medium
Compare ARIMA and Prophet for time series forecasting. What are the pros and cons of each?
#ARIMA
#Prophet
#Forecasting
Data Scientist
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Technical
•
easy
What is the time complexity of looking up a value in a Python list versus a Python dictionary? Why?
#Python
#Time Complexity
#Hash Tables
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