Top 14 Bayer Interview Questions + Guide in 2024

Bayer is a global leader in the Life Sciences sectors, with a strong presence in both healthcare and agriculture. Their mission goes beyond the confines of traditional business, aiming to make the vision of “Health for All. Hunger for None” a tangible reality for everyone.

To stay a leader in these fields, Bayer has placed immense importance on data to drive their operations. If you’re seeking job opportunities in data analysis, whether in research or logistics, Bayer is likely to offer numerous prospects. Here are some key points to keep in mind when preparing for an interview at Bayer.

If you’re looking for guidance to ace your upcoming interview or plan to apply for the role, you’ve come to the right place. We will cover the stages of the interview process, our handpicked Bayer interview questions, and strategies for answering them.

Round 1: Application

Your journey begins with an application in mid-February, although they sometimes open up roles outside of this hiring cycle. Bayer looks for someone with a good background in any of the following fields: data science, engineering, analytics, and biology. However, do not get discouraged if you don’t hear back immediately, as it may take some time before you get a response.

Round 2: Phone Screening

The first stage of the interview is the phone screening, typically scheduled for early March. During this stage, you will discuss your skills, experiences, and the expectations for the position.

Round 3: Panel Interview

If the phone screening goes well, you’ll be invited to a panel interview, usually taking place in early April. The panel members are friendly and may come from both a data science and a biological background.

Round 4: Second Interview and Take-Home Challenge

Following the panel interview, there are several rounds of interviews which include a take-home challenge and a presentation with Q&A. The take-home challenge tests your technical abilities relevant to the job role, while the presentation is an opportunity to showcase your communication skills and knowledge.

Round 5: Further Interviews

After the take-home challenge, you can expect around three to four more interviews. One of these will be technical and focused on your experiences, with a mini case study included. The remaining interviews are behavioral and aim to assess your ability to fit into the company’s culture.

The entire process could require approximately 4 hours of interviews in total.

As a data-driven company, Bayer leverages machine learning to enhance its research capabilities, optimize supply chain processes, and personalize patient care. Machine learning plays a pivotal role in Bayer’s commitment to innovation and its pursuit of a healthier world.

For prospective hires at Bayer, having a solid background in machine learning is not just an advantage—it’s essential. This is evident as machine learning questions form a significant part of the evaluation, appearing in 50% of Bayer job interviews. Here are some questions that you might encounter:

1. How does random forest generate the forest and why use it over logistic regression?

Random forest is a popular machine learning algorithm. Explain how it generates the forest and discuss why one might choose to use it over other algorithms like logistic regression.

2. What are the key differences between classification and regression models?

Describe the main differences between classification models and regression models.

3. How to adjust the output probabilities of a binary classifier trained on a downsampled dataset for use on the total population?

Suppose you’re training a binary classification algorithm on a downsampled dataset where 99.8% of individuals have a value of 0 and 0.2% have a value of 1. After training the model on this smaller sample, how would you adjust the output probabilities to apply this model to the total population?

4. How would you explain the bias-variance tradeoff with regards to building and choosing a model to use?

Imagine you are asked to build a machine learning model to decide new loan approvals for a financial firm. You ask the data department in the company for a subset of data to get started working on the problem. The data includes different features about applicants such as age, occupation, zip code, height, number of children, favorite color, etc. You decide to build multiple machine-learning models to test out different ideas before settling on the best one.

5. What’s the difference between Lasso and Ridge Regression?

Both Lasso and Ridge regressions add a penalty term to the loss function of regression to prevent over-fitting of parameters.

Practically, Lasso models perform better when there are many features that don’t have a strong effect on the dependent variable. This is because of the “diamond” shape of Lasso’s regression penalty term.

To get ready for machine learning interview questions, we recommend taking the machine learning course.

As a global enterprise with core competencies in the life science fields of health care and agriculture, whose impacts are broad, deep, and critical to get right, Bayer places a strong emphasis on the application of probability and statistics in its decision-making processes. These disciplines are foundational to the company’s research and development, quality control, and market analysis.

As such, interviewees vying for roles that require statistical acumen can expect to be tested on their knowledge and application of probability and statistical concepts. The questions aim to assess not just theoretical understanding but also the ability to apply these concepts to real-world scenarios, reflecting Bayer’s practical approach to problem-solving. Here are some sample questions that might be posed during an interview:

6. Is the coin fair based on the results of 10 flips?

You flip a coin 10 times and it comes up tails 8 times and heads twice. Based on these results, determine if the coin is fair.

7. How many students are expected to have actually won the coin-tossing game?

In a game where 100 students toss a coin, if it comes up heads, they win. If it comes up tails, they toss again. If it comes up heads the second time, they lie about winning. If it comes up tails, they admit to losing. Given that 30 students claimed to have won, estimate the actual number of winners.

8. What are the logistic and softmax functions, their differences, and their usefulness in logistic regression?

Define the logistic and softmax functions, explain the difference between the two, and discuss why they are useful in logistic regression.

To prepare for Probability & Statistics questions, consider using the statistics and A/B testing learning path and the probability learning path. These resources cover a wide range of topics, from basic statistics to advanced probability concepts.

9. How would you write a function to find the moving window average?

Given a list of numbers nums and an integer window_size, write a function moving_window to find the moving window average. Provide examples of your function in action.

10. How would you write a function to determine if two strings are anagrams?

Given two strings, write a function to return True if the strings are anagrams of each other and False if they are not. Note that a word is not an anagram of itself. Provide examples of your function in action.

11. How would you write a function to search a linked list for a target value?

Write a function, search_list, that returns a boolean indicating if the target value is in the linked_list or not. You receive the head of the linked list, which is a dictionary with the following keys: value (contains the value of the node) and next (contains the next node in the list, or None). If the linked list is empty, you’ll receive None since there is no head node for an empty list. Provide an example of your function in action.

To practice Algorithms interview questions, consider using the Python learning path or the full list of Algorithms questions in our database.

With vast amounts of data generated across its various departments, the ability to query, analyze, and derive insights from Bayer’s data is paramount.

SQL is one of the primary tools used by Bayer’s data professionals to interact with databases and extract meaningful information. As a result, candidates applying for data-centric roles at Bayer can expect to be evaluated on their SQL proficiency. Here are some representative SQL questions that Bayer might pose during their interview process:

12. How would you use SQL to answer questions about transactions in the annual_payments table?

We have an annual_payments table. Write SQL queries to answer the following questions:

A. How many total transactions are in this table?

B. How many different users made transactions?

C. How many transactions listed as "paid" have an amount greater or equal to 100?

D. Which product made the highest revenue? (use only transactions with a "paid" status)

13. How would you write a query to find users who are currently “Excited” and have never been “Bored” with an ad campaign?

You work at an advertising firm and have a table of users’ impressions of ad campaigns over time. Each impression_id consists of values of user engagement specified by Excited, OK, and Bored. Write a query to find all users that are currently “Excited” and have never, ever been “Bored” with a campaign.

14. How would you write a query to get the total amount spent on each item by users who registered in 2022?

You work at Costco, which has a users table with user information, including their registration date, and a purchases table with the entire item purchase history for those users. Write a query to get the total amount spent on each item in the ‘purchases’ table by users that registered in 2022.

To continue practicing, try the SQL learning path and the full list of SQL questions and solutions in our interview questions database.