Amgen Data Analyst Interview Questions + Guide in 2025

Amgen is a leading biotechnology company dedicated to serving patients and transforming lives through innovative therapies.

The Data Analyst role at Amgen involves leveraging analytical skills to support strategic decision-making and drive performance insights across various brands and therapeutic areas. Key responsibilities include designing and implementing data analytics approaches, synthesizing findings from complex datasets, and presenting actionable insights to stakeholders, including senior leadership. A successful candidate will possess strong analytical capabilities, project management skills, and the ability to communicate complex concepts effectively. Moreover, familiarity with secondary data sources, statistical methodologies, and cross-functional collaboration is essential for thriving in Amgen's values-driven organization, which prioritizes patient care and employee growth.

This guide aims to equip you with tailored insights and strategies to excel in your interview process at Amgen, ensuring you can demonstrate both your technical expertise and alignment with the company's mission.

The interview process for a Data Analyst position at Amgen is structured and thorough, designed to assess both technical and interpersonal skills. Candidates can expect a multi-step process that includes several rounds of interviews, focusing on both behavioral and technical competencies.

1. Initial Phone Screen

The process typically begins with a phone screening conducted by a recruiter or HR representative. This initial conversation lasts about 30 minutes and focuses on your background, experiences, and motivations for applying to Amgen. Expect standard HR questions, such as inquiries about your work history and whether you will require visa sponsorship in the future.

2. Technical Assessment

Following the initial screen, candidates may be required to complete a technical assessment. This could involve a coding test or a data analysis task, often conducted through platforms like HackerRank. The assessment aims to evaluate your analytical skills, familiarity with data manipulation, and proficiency in relevant programming languages such as SQL or Python.

3. Behavioral Interviews

Candidates who pass the technical assessment will typically move on to a series of behavioral interviews. These interviews may be conducted one-on-one or in a panel format, involving team members from various departments. Expect to discuss your past experiences, how you handle challenges, and your approach to teamwork and project management. The interviews are designed to gauge your fit within Amgen's collaborative culture and your ability to communicate effectively with cross-functional teams.

4. Onsite Interviews

For those who progress further, an onsite interview may be scheduled. This usually consists of multiple rounds of interviews with different team members, including managers and senior leadership. Each interview lasts approximately 30 to 45 minutes and covers both technical and behavioral questions. Candidates may also be asked to present a case study or a previous project to demonstrate their analytical thinking and presentation skills.

5. Final Interview

The final stage often includes a discussion with higher-level management or executives. This interview focuses on your long-term career goals, your understanding of Amgen's mission, and how you can contribute to the company's objectives. It is also an opportunity for you to ask questions about the team dynamics and the company's future direction.

As you prepare for your interview, be ready to discuss your experiences in detail and how they relate to the responsibilities of a Data Analyst at Amgen. Next, let's delve into the specific interview questions that candidates have encountered during the process.

Here are some tips to help you excel in your interview.

Understand the Company Culture

Amgen is a values-based organization with a strong mission to serve patients. Familiarize yourself with their core values and how they translate into everyday work. During your interview, demonstrate how your personal values align with Amgen's mission. This will not only show your enthusiasm for the role but also your commitment to contributing positively to the company culture.

Prepare for Behavioral Questions

Expect a significant focus on behavioral interview questions. Prepare to share specific examples from your past experiences that highlight your problem-solving skills, teamwork, and ability to handle challenges. Use the STAR method (Situation, Task, Action, Result) to structure your responses, ensuring you convey the impact of your actions clearly.

Showcase Your Analytical Skills

As a Data Analyst, your technical skills will be under scrutiny. Be ready to discuss your experience with data analytics tools and methodologies. Highlight any specific projects where you successfully analyzed complex data sets and derived actionable insights. If possible, bring examples of your work or case studies that demonstrate your analytical capabilities.

Be Ready for Cross-Functional Collaboration Questions

Amgen values collaboration across teams. Prepare to discuss your experience working with cross-functional teams, particularly in synthesizing findings and developing recommendations. Be specific about how you navigated different perspectives and how your contributions led to successful outcomes.

Anticipate Technical Assessments

While the interview process may include behavioral questions, be prepared for technical assessments as well. Brush up on your knowledge of data analysis techniques, statistical methods, and any relevant software tools. If you have experience with SQL or other programming languages, be ready to discuss how you've applied these skills in your previous roles.

Communicate Clearly and Effectively

Strong oral and written communication skills are essential for this role. Practice explaining complex concepts in a clear and concise manner. You may be asked to present your findings or recommendations, so consider preparing a brief presentation that showcases your analytical work and how it can benefit Amgen.

Follow Up Professionally

After your interview, send a thank-you email to express your appreciation for the opportunity to interview. Reiterate your interest in the position and briefly mention how you can contribute to Amgen's mission. This not only shows professionalism but also keeps you top of mind for the interviewers.

By following these tips, you can present yourself as a well-prepared and enthusiastic candidate who is ready to contribute to Amgen's mission of serving patients. Good luck!

In this section, we’ll review the various interview questions that might be asked during a Data Analyst interview at Amgen. The interview process will likely focus on your analytical skills, problem-solving abilities, and experience with data management and reporting. Be prepared to discuss your past experiences, technical skills, and how you can contribute to Amgen's mission of serving patients.

Experience and Background

1. Can you describe a project where you had to analyze complex data sets? What was your approach?

This question assesses your hands-on experience with data analysis and your problem-solving skills.

How to Answer

Discuss a specific project, detailing the data sources you used, the analytical methods you applied, and the outcomes of your analysis. Highlight any challenges you faced and how you overcame them.

Example

“In my previous role, I worked on a project analyzing patient data from electronic medical records. I utilized SQL to extract relevant data, then applied statistical methods to identify trends in patient outcomes. This analysis led to actionable insights that improved our treatment protocols.”

2. How do you prioritize multiple projects with competing deadlines?

This question evaluates your time management and organizational skills.

How to Answer

Explain your process for assessing project urgency and importance, and how you communicate with stakeholders to manage expectations.

Example

“I prioritize projects by assessing their impact on business goals and deadlines. I use project management tools to track progress and communicate regularly with stakeholders to ensure alignment. For instance, when faced with overlapping deadlines, I negotiated timelines with my team to ensure critical projects were completed on time.”

Technical Skills

3. What tools and technologies are you familiar with for data analysis?

This question gauges your technical proficiency and familiarity with industry-standard tools.

How to Answer

List the tools you have experience with, such as SQL, Python, R, Excel, or any data visualization software. Provide examples of how you have used these tools in your work.

Example

“I am proficient in SQL for database management and have used Python for data analysis and automation. Additionally, I have experience with Tableau for data visualization, which I used to create dashboards that helped stakeholders understand key metrics at a glance.”

4. Can you explain the difference between structured and unstructured data?

This question tests your understanding of data types and their implications for analysis.

How to Answer

Define both terms clearly and provide examples of each, along with how you would handle them in a data analysis context.

Example

“Structured data is organized and easily searchable, typically found in relational databases, such as customer records. Unstructured data, on the other hand, is not organized in a predefined manner, like emails or social media posts. For unstructured data, I would use text analysis techniques to extract meaningful insights.”

Behavioral Questions

5. Describe a time when you had to communicate complex data findings to a non-technical audience.

This question assesses your communication skills and ability to convey technical information effectively.

How to Answer

Share a specific instance where you simplified complex data for a non-technical audience, focusing on your approach and the outcome.

Example

“I once presented a data analysis report to a group of marketing professionals. I focused on visual aids, such as charts and graphs, to illustrate key points. By avoiding technical jargon and relating the data to their marketing strategies, I ensured they understood the implications of the findings.”

6. How do you handle feedback or criticism regarding your analysis?

This question evaluates your ability to accept feedback and improve your work.

How to Answer

Discuss your approach to receiving feedback, emphasizing your willingness to learn and adapt.

Example

“I view feedback as an opportunity for growth. When I receive criticism, I take the time to understand the perspective of the reviewer and assess how I can improve my analysis. For example, after receiving feedback on a report, I revised my methodology and incorporated additional data sources, which enhanced the overall quality of my work.”

Problem-Solving

7. What steps would you take if you discovered an error in your analysis after presenting it?

This question tests your integrity and problem-solving skills.

How to Answer

Outline the steps you would take to address the error, including how you would communicate it to stakeholders.

Example

“If I discovered an error post-presentation, I would first verify the mistake and assess its impact. I would then promptly inform the stakeholders, provide a corrected analysis, and discuss the implications. Transparency is key, and I believe it’s important to take responsibility and ensure that the correct information is available.”

8. Can you give an example of how you used data to influence a business decision?

This question assesses your ability to leverage data for strategic decision-making.

How to Answer

Describe a specific instance where your data analysis led to a significant business decision, detailing the process and outcome.

Example

“In a previous role, I analyzed customer feedback data to identify trends in product satisfaction. My findings revealed a common issue that was affecting customer retention. I presented this data to the product team, which led to changes in the product design, ultimately increasing customer satisfaction and retention rates.”