This time Roblox DS Summer Intern OA is divided into 4 parts: the first two parts are interactive game tests, the third part is behavioral multiple-choice questions, and the fourth part is coding. The overall style is different from traditional data post online testing, which places more emphasis on logical decision-making, resource planning and rapid trial and error capabilities.
Part One: Car Building Game
It lasts 25 minutes, with two sections (13 minutes each), each with different terrain. The task is to install a limited number of parts on a car so that it can successfully pass obstacles. The goal is to create as many "successful vehicles" as possible.
The functions of components are designed to be relatively abstract, and many times the effects cannot be understood immediately after reading the description. The recommended approach is: don’t bother with the explanation, just install it and test it, and then use replay to see the actual performance. The understanding speed will be much faster.
Also note - the effects may be completely different depending on where the components are installed, so it's important to try multiple combinations. There is almost no fixed strategy here, because everyone gets different terrain and components. The whole process is a process of constant trial and error → adjustment → try again. It is recommended to clear the first terrain first and then challenge the second one.
Resource management is also a key point: each component consumed consumes energy, and a vehicle can only be equipped with up to 3 components, so you need to think about how to cover more functions within a limited configuration.
A pitfall that is easily overlooked is that some components need to be used together to be effective. If you can't run for a long time, it is likely that the combination is not matched. I only discovered this in the last few minutes.
Part 2: Factory production of toys
Same 25 minutes, but only one section. The core goal is: Maximize earnings within 24 hours.
You need to start by buying raw materials, gradually making parts, synthesizing components, and finally completing four different toys. The profit of each toy is different, so you must first calculate the cost and selling price before deciding which production line to promote.
The difficulty lies mainly in pipeline collaboration:
- Different parts have different production times
- Materials required vary in quantity
- Some components must wait until all materials are available before production can begin
If a component exceeds the storage capacity after being produced and is not consumed in time, it will be directly wasted, which will greatly affect the final revenue.
Another typical stuck point is "capacity mismatch": some high-end components require a large number of small parts, but the maximum output of small parts cannot keep up, which will slow down the entire line. So, the production ratio must be continuously adjusted to match each link as much as possible.
The system also provides a buff mechanism. You can choose to double output or reduce demand, but it will increase costs, so it is essentially a question of ROI judgment - it is not about adding if you can, but to see whether it really increases the final profit.
Part 3: Behavioral Multiple Choice Questions
This section is 25 minutes long and has 23 questions in total. Each question will give a workplace scenario and provide 4 approaches, allowing you to choose an optimal solution and a worst solution. Common situations include: whether you should point out problems in the process, what to do if you have different opinions from colleagues, whether you should take the initiative to promote improvements, etc.
In summary, it's more like a personality and workplace judgment test, with no particularly "standard" correct answers. But there is an obvious pattern: the worst options are usually not proactive enough, such as choosing to avoid the problem, not communicating at all, or shifting the responsibility to others.
When answering questions, you can give priority to those options that reflect ownership, communication awareness and teamwork. Even if you are not sure which one is the best, if you first eliminate obviously negative or inactive answers, the accuracy rate will usually not be too low.
Part 4: Coding
Coding is a total of 50 minutes, 4 questions, completed on CodeSignal, supports Python or R. The overall difficulty is not particularly high, but it focuses more on the basics of data analysis and statistical understanding rather than pure algorithms.
The first question is a basic statistics question. Given a numeric array, significance level, power, and effect size to be detected, a two-sample z-test is required to calculate the required sample size. The essence is to examine the relationship between the core parameters of hypothesis testing. As long as the formula is familiar, it is not difficult.
The second question provides three arrays: period, group, and outcome, which need to calculate difference-in-differences. There is also a trend validation to determine whether the pre-period difference falls within a given threshold. The focus is on understanding the logic of DID, rather than complicated implementation - first calculate the changes in treatment and control before and after, and then compare the differences between the two.
Learn more
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