I've been getting a lot of questions from students lately:Merck What are the Tech Post OA tests for these traditional pharma giants? Is it difficult? In fact, although it is a healthcare company, Merck's tech post is a standard tech company process, and the OA part looks at the algorithm foundation, but also there is no lack of examination of code details. Today we will organize a Merck OA full strategy to help you quickly figure out the routine and prepare in advance!
Merck OA Process Overview
Although Merck is a traditional pharmaceutical company, Merck's technical recruitment process is very standardized and technologically advanced, and OA is mostly conducted through third-party platforms such as Codility or HackerRank, so the exam experience is basically the same as that of large companies.
The overall length of the exam is usually 60 to 90 minutes and consists of 2 to 3 programming questions, which are designed to be "practical + rigorous", testing basic algorithmic skills as well as emphasizing code robustness, boundary handling, and readability.
According to the feedback from the students, most of the questions are in the range of LeetCode Medium~Hard, but are more oriented to "engineering thinking": for example, how to simulate the behavior of the system based on the input data, and how to implement a certain business logic processing module, etc. The participants' feedback indicates that the questions are mostly in the range of LeetCode Medium~Hard.
In terms of platform operation, both Codility and HackerRank automatically detect syntax errors, run sample tests, and validate hidden test samples after submission, focusing on whether the code remains stable under extreme data and boundary scenarios.
In addition, some questions require you to design your own input/output format, and it is recommended that you familiarize yourself with the interview platform interface as early as possible to avoid wasting time on question comprehension and format checking. Be sure to set aside 10~15 minutes for test sample verification + debug submission, and don't spend too much time on the main logic implementation.
Merck OA Real Questions Sharing
Question 1
You are the Chief Data Scientist of an e-commerce website. In order to predict how much money a customer will spend on your company's platform, you build a multiple linear regression model on your customers' purchasing activity based on 100 variables. In order to predict how much money a customer will spend on your company's platform , you build a multiple linear regression model on your customers' purchasing activity based on 100 variables.
Assume that the number of observations (i.e. data points) greatly exceeds the number of variables. After fitting your data using an Ordinary Least- Squares (OLS) approach you observe that one of your variables has a p-value of 0.03. Squares (OLS) approach, you observe that one of your variables has a p-value of 0.03.
Which of the following can you infer about the relationship between this variable and the amount a customer will spend?
A. The low p-value implies that there may be a link between the variable and the amount a customer will spend, but you cannot say anything about causation
B. The low p-value implies that it is very unlikely that the observed relationship between the variable and the amount a customer will spend is due to random chance
C. The low p-value implies that the variable explains most of the variation between the amounts that different customers will spend
D. The low p-value does not necessarily say anything significant about the relationship between the variable and the amount a customer will spend
Select one.
- 1 only
- 4 only
- 1 and 2 only
- 2 and 3 only
Question 2
Consider the following two scientific problems.
- Identifying defective airbags
- Announcing whether the atmosphere of some remote planet contains water based on observational evidence.
Which of the following statements is MOST accurate? (Note: Precision is the ratio of true positives to all predicted positives, recall is the ratio of true positives to all actual positives, and accuracy is the ratio of true positives and negatives to all actual positives and negatives. positives to all actual positives, and accuracy is the ratio of true positives and negatives to all actual positives and negatives.)
Select one.
A) Airbag testing needs high recall, and water identification needs high precision
B) Airbag testing needs high precision, and water identification needs high recall
C) Both scenarios need to maximize the average of precision and recall
D) Both scenarios need to maximize the accuracy
E) Both scenarios need to maximize the precision
Question 3
Which model best describes the independence assumptions in Naive Bayes inference for features {X₁, X₂} and class label Y?
Select one.
Question 4
You want to build a model that predicts the next line of code you type. You want millions of points of training data, but you only have a few thousand files with You want millions of points of training data, but you only have a few thousand files with a few thousand lines each.
What type of training data would be best to use?
Select one.
A) Your model takes as input an entire text file with one missing line, and outputs a prediction of that missing line
B) Your model takes as input the top k lines of a file and outputs the k + 1st line
C) Your model takes as input the last k lines and either a fake or real previous line, and predicts whether or not that preceding line is real or fake
D) Your model takes as input all the function signatures of the code, and predicts, given random lines from the dataset, whether they appear in the same file or not
E) Your model takes as input one random line from the code, and tries to predict the line that comes after
Question 5
You are building a decision tree and want to choose the attribute which gives the most informative splitting between two classes, A and B. The nodes corresponding to the attributes are used to classify four data points from A and four data points from B. corresponding to the attributes are used to classify four data points from A and four data points from B. The nodes corresponding to the attributes are used to classify the two classes, A and B.
If each node has exactly two children, which of the following decisions yields the MOST information gain?
Select one.
A) The one that sends 3 data points from A and 2 data points from B to the left node
B) The one that sends 2 data points from each class to the right node
C) The one that sends 3 data points from each class to the right node
D) The one that sends 0 data points from A to the right node and 3 data points from B to the left node
E) The one that sends 2 data points from A to the right node and 4 data points from B to the left node
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