Mckesson
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Interview Questions
Practice with real questions asked in interviews. Click any card to reveal the answer.
Technical Questions
Infinite Scroll - Implement infinite scrolling with virtualization
Approach & Solution
Approach: Consider time/space complexity, edge cases, and explain your thought process clearly. Sign up to access detailed solutions!
Clone Graph - Create a deep copy of an undirected graph
Approach & Solution
Approach: Consider time/space complexity, edge cases, and explain your thought process clearly. Sign up to access detailed solutions!
LRU Cache - Design a data structure for Least Recently Used cache
Approach & Solution
Approach: Consider time/space complexity, edge cases, and explain your thought process clearly. Sign up to access detailed solutions!
Behavioral Questions
Give an example of when you had to make a difficult trade-off decision
Sample Answer (STAR Method)
Task: I needed to decide which feature to prioritize, as we only had time to properly implement one.
Action: I analyzed user feedback from our beta testers and found that 80% of users mentioned wanting notifications, while only 30% mentioned search filters. I presented data to the team showing that notifications would provide more value. I also proposed a simpler basic search that we could implement in 2 days, allowing us to deliver both features in limited form.
Result: We implemented full notification functionality and basic search. User satisfaction scores in our final presentation were 4.5/5. This taught me to make data-driven decisions focused on user needs, and to look for creative solutions that don't require choosing between extremes.
How do you handle tight deadlines and pressure?
Sample Answer (STAR Method)
Task: I needed to manage my time effectively to complete everything without compromising quality.
Action: I started by listing all tasks and estimating time for each. I prioritized based on due dates and complexity, then created a detailed schedule with specific time blocks. I eliminated distractions by working in the library, used the Pomodoro Technique for focused coding sessions, and took strategic breaks to avoid burnout. When I realized one assignment was taking longer than expected, I reached out to the TA for clarification rather than spending hours debugging alone.
Result: I completed all assignments on time and performed well on my exams. This experience taught me the importance of planning, prioritization, and knowing when to seek help. I now proactively manage my schedule to avoid such situations, but I'm confident in my ability to perform under pressure when necessary.
Mckesson McKesson Data Scientist and Machine Learning Engineer Intern Interview Questions Interview Process 2026
The Mckesson McKesson Data Scientist and Machine Learning Engineer Intern Interview Questions interview typically consists of 220+ technical questions covering algorithms, data structures, and system design. Located in Remote, this position offers hands-on experience with cutting-edge technology and mentorship from senior engineers.
Key interview stages include: initial screening, technical coding rounds focusing on Software Development, System Design, Behavioral, and final rounds with team leads. The difficulty level is rated as Mediumwithin the Enterprise tier.
Essential Skills for Mckesson McKesson Data Scientist and Machine Learning Engineer Intern Interview Questions Role
Technical Skills
- Python
- SQL
- Data Analysis
- Statistics
Interview Topics
- Software Development
- System Design
- Behavioral
What Makes Mckesson Different
Mckesson is known for its collaborative environment and meaningful impact. Interns work on real production systems and contribute to projects used by millions of users.
The company offers comprehensive learning opportunities, including mentorship programs, technical talks, and hands-on experience with industry-leading tools and frameworks.McKesson Data Scientist and Machine Learning Engineer Intern Interview Questions interns typically work in Remote with hybrid flexibility.
Frequently Asked Questions
How difficult is the Mckesson McKesson Data Scientist and Machine Learning Engineer Intern Interview Questions interview?
The interview is rated as Medium difficulty. Candidates should prepare for 220+ practice questions covering algorithms, data structures, and system design fundamentals.
What programming languages are accepted?
Most candidates use Python, Java, C++, or JavaScript. Choose the language you're most comfortable with for optimal performance during coding rounds.
How long is the Mckesson interview process?
The process typically takes 2-4 weeks from initial application to final decision, including phone screens, technical rounds, and team interviews.
Mckesson McKesson Data Scientist and Machine Learning Engineer Intern Interview Questions salary and benefits
Mckesson offers competitive compensation packages for McKesson Data Scientist and Machine Learning Engineer Intern Interview Questions positions in Remote. Benefits include health insurance, learning stipends, mentorship programs, and potential full-time conversion opportunities.
Best preparation resources for Mckesson interviews
Practice coding problems on LeetCode, study system design fundamentals, review computer science concepts, and prepare behavioral questions using the STAR method. Focus on Software Development, System Design, Behavioral.
Mckesson Internship Program 2026
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