Amgen Data Scientist Interview Questions + Guide in 2024

Amgen is a pioneering biotechnology company dedicated to unlocking the potential of biology for patients suffering from serious illnesses. With a mission to serve patients, Amgen has become one of the world’s leading biotechnology companies, reaching over 10 million patients worldwide.

As a Senior Data Scientist at Amgen, you will play a crucial role in the forefront of digital transformation within the biopharmaceutical industry. The position involves driving the development and integration of cutting-edge digital tools, optimizing data analytics, and leading cross-functional teams.

If you’re ready to innovate and make a significant impact in healthcare, this guide will help you through the interview process, commonly asked Amgen data scientist interview questions, and some tips to make your preparation better.

Recruiter/Hiring Manager Call Screening

If your CV is among the shortlisted few, a recruiter from the Amgen Talent Acquisition Team will contact you and verify key details like your experiences and skill level. Behavioral questions may also be part of the screening process.

Sometimes, the hiring manager stays present during the screening round to answer your queries about the role and the company itself. They may also indulge in surface-level technical and behavioral discussions.

The whole recruiter call should take about 30 minutes.

Technical Virtual Interview

Successfully navigating the recruiter round will invite you to the technical screening round. Technical screening for the data scientist role is usually conducted through virtual means, including video conference and screen sharing. Questions in this one-hour interview stage may cover statistics, SQL, machine learning, and case studies related to predicting new drug prescriptions.

Onsite Interview Rounds

After a second recruiter call outlining the next stage, you’ll be invited to attend the on-site interview loop. During your day at the Amgen office, multiple interview rounds, varying with the role, will be conducted. Your technical prowess, including programming and machine learning modeling capabilities, will be evaluated against the finalized candidates throughout these interviews.

Typically, the interview varies by role and team, but commonly, data scientist interviews follow a fairly standardized process across these question topics.

1. Write a function calculate_rmse to calculate the root mean squared error of a regression model.

The function should take in two lists, one that represents the predictions y_pred and another with the target values y_true.

2. Write a query to get the last transaction for each day from a table of bank transactions.

Given a table of bank transactions with columns id, transaction_value, and created_at, write a query to get the last transaction for each day. The output should include the id of the transaction, datetime of the transaction, and the transaction amount. Order the transactions by datetime.

3. Write a function random_key that returns a key at random with a probability proportional to the weights.

Given a dictionary with weights, write a function random_key that returns a key at random with a probability proportional to the weights.

4. Write a function to get a sample from a standard normal distribution.

Create a function to generate a sample from a standard normal distribution.

5. Write a function nearest_entries to find the closest element to N and return k-next and k-previous elements.

Given a sorted list of integers ints with no duplicates, write an efficient function nearest_entries that takes in integers N and k and returns the element closest to N along with the k-next and k-previous elements of the list.

6. How would you explain what a p-value is to someone who is not technical?

Explain the concept of a p-value in simple terms to someone without a technical background. Use analogies or everyday examples to make it understandable.

7. How many more samples would we need to decrease the margin of error from 3 to 0.3?

Given a sample size (n) with a margin of error of 3, calculate the additional number of samples required to reduce the margin of error to 0.3.

8. How would you determine if the results of an AB test on a landing page redesign are statistically significant?

Describe the process of analyzing AB test results to determine if the observed differences in click-through rates are statistically significant. Include steps such as hypothesis testing and p-value calculation.

9. What metrics/graphs/models would you use to analyze churn behavior for Netflix’s pricing plans?

Netflix has two pricing plans: $15/month or $100/year. An executive wants to analyze the churn behavior of users subscribing to either plan. What kinds of metrics, graphs, or models would you build to provide an overarching view of subscription performance?

10. How would you build a model to predict which merchants DoorDash should acquire in a new market?

As a data scientist at DoorDash, how would you build a model to predict which merchants the company should target for acquisition when entering a new market?

11. How would you value the benefit of keeping a hit TV show on Netflix?

Netflix executives are considering renewing a deal with another TV network for exclusive streaming rights to a hit TV series. The show has been on Netflix for a year. How would you approach valuing the benefit of keeping this show on Netflix?

12. How would you measure the success of LinkedIn’s newsfeed ranking algorithm?

As a data scientist on the engagement team, how would you measure the success of LinkedIn’s newsfeed ranking algorithm? Additionally, if some success metrics are improving while others are declining, how would you approach this situation?

13. How would you assign point values to letters in Spanish Scrabble without knowing Spanish?

If you need to build Scrabble for Spanish users and don’t know Spanish, how would you determine the point values for each letter?

Here are some quick tips to help you stand out during interviews:

• Refresh Machine Learning Fundamentals: Amgen significantly emphasizes machine learning background. Make sure you are comfortable with prediction models and can articulate your approach to the machine learning interview questions you’ll get asked.

• Understand Healthcare Data: Familiarize yourself with medical data, such as drug prescription data, as you may be asked questions related to healthcare analytics. You can also try these healthcare data science projects to become more familiar with how these data work.

• Be Prepared for Behavioral Questions: Given that some candidates focused extensively on behavioral questions, be ready to discuss past experiences, especially those involving hardships and how you overcame them.

What is the average salary for a Data Scientist at Amgen?

What is the company culture like at Amgen?

Amgen is committed to innovation and collaboration, aiming to make a significant impact in the biopharmaceutical industry. The company fosters a supportive work environment that values continuous learning, mentoring, and professional growth. Employees work together to serve patients and achieve organizational goals.

What can I expect in terms of professional growth and benefits at Amgen?

Amgen offers a comprehensive Total Rewards Plan, including health and welfare plans, retirement savings plans, and career development opportunities. Employees can also benefit from flexible work models, stock-based incentives, annual bonuses, and award-winning time-off plans.

Landing a position as a Data Scientist at Amgen is an exciting opportunity to be at the forefront of biopharmaceutical innovation and digital transformation, and we hope this interview guide is helpful for your preparation.

For more information about Amgen, please refer to our main interview guide, which provides extensive details about the company and its interview process for tech positions.

Good luck with your interview!