Role: Data Scientist
College: Not Specified
Interview Date: August 2025
Interview Type: Full-Time
Result: Not Specified
Difficulty: Difficult
Rounds: 4 rounds
Topics Asked: Predictive Modeling, Data Visualization, Python, Pandas, System Design (Data Pipeline for Clinical Trials), ETL Processes, Machine Learning, Statistical Analysis, Team Collaboration, Problem-Solving (STAR methodology)
Experience:
The candidate started preparation a month before the interview, focusing on Python and machine learning skills using Kaggle and online courses, and reviewing Amgen's recent publications.
The interview process consisted of 4 rounds over a month.
- Round 1: Initial Phone Screen
Focused on explaining experiences with predictive modeling and data visualization. The interviewer was knowledgeable and provided insights into Amgen's data initiatives.
- Round 2: Technical Round (Hands-on Coding)
Involved hands-on coding exercises using a shared online development environment. This phase was critical, spanning nearly two hours and requiring thorough scripting in Python and data manipulation using Pandas.
- Round 3: System Design
The candidate was asked to design a data pipeline for clinical trials data, requiring careful architectural choices and an understanding of ETL processes. Specific questions included:
- How would you implement a recommendation system for personalized medicine using machine learning? (Answer involved collaborative filtering and patient data)
- Design a scalable data processing pipeline for genomic sequencer data.
- Write a Python script to calculate the statistical percentile of a list of numbers.
- Round 4: Behavioral Interview
Focused on team collaboration and problem-solving through the STAR methodology. A question asked was:
- Tell me about a time you worked in a team setting and resolved a conflict using your experience. (Answer involved initiating a meeting, discussing reservations, brainstorming solutions, and redistributing tasks based on strengths, emphasizing communication)
Amgen utilized Zoom for virtual interactions and provided feedback promptly between rounds. The overall process was rigorous but clearly structured, offering ample opportunity to demonstrate technical skills and enthusiasm for Amgen's mission.