The data science case study interview is usually the last step in a long and arduous process. This may be at a consulting firm that offers its consulting services to different companies looking for business guidance. Or, it may be at a company looking to hire an in-house data scientist to help guide strategy decisions and improve the company’s performance. If you’re prepping for a data science case study interview, you probably have expertise in the field of data science. But that doesn’t necessarily mean you have all the skills you need to ace the interview. Here we’ll look in more detail at what you need to prepare for the case study part of the interview and land that dream job.
Data Science vs. Regular Case Interview: What’s the Difference?
Most working consultants have to go through a case study as part of their interview process. There’s a lot of information out there about how to handle a regular case study. This involves being given a sample problem that represents what real-world businesses encounter all the time. It may even be taken from an actual client of the firm doing the hiring. Case interview coaching is a popular service that helps interviewees prepare.
The data science case study is a specialized version of this. Job candidates who have made it through previous rounds of interviews will be given the chance to prove their ability to perform in a way that fits what the hiring company is looking for.
Data Science Case Interview
The data science case study will involve conducting a real data science task. This task may be completed over the course of an afternoon, or applicants may be given several days to analyze the problem and prepare a presentation. There is likely to be a significant amount of Q&A involved with the presentation. The point is not only to test your data science expertise. It will also test your ability to apply that expertise to real business scenarios and to communicate with coworkers and clients.
Here are is a typical data science case study interview example. They might involve being presented with a scenario in which a client is facing a challenge with an existing product. Alternatively, the client may be considering ways to expand services. You will be given a data set, which may consist of several subsets. These subsets will present their own challenges. Some may be formatted differently, or may have messy, ambiguous, or obviously incorrect figures.
Your job will be to analyze this data and derive insights that enable you to advise the client in the particular challenge they’re facing. You will be asked to formally present your data to interviewers and to field their questions. Importantly, these case studies are designed to test your ability to think critically and creatively—they are open-ended, with no single correct responses. This sometimes throws off quantitative personality types who are used to being able to come up with a right answer.
Data Science Case Study Interview Example
These case studies often involve real scenarios, or at least simulations of the exact kinds of scenarios real companies are likely to face. Here’s one example of the kind of data science case study you might be asked to work with.
Facebook is considering acquiring a music-sharing startup. Facebook executives want to know whether bringing the startup onto Facebook’s platform will increase its user base and increase overall revenues.
You will be provided with a data set that includes certain information. This information could include the user bases of both Facebook and this music-sharing platform. This data will also include demographic information and user engagement numbers for both Facebook and the music-sharing platform.
Some information may be missing from the startup’s figures. If so, you may have to guess or project those figures based on other comparable companies’ performance. The data set will also include information about the operational costs of the startup. Additionally, the performance of other acquisitions Facebook has made. Your job will be to analyze all this data and project the effects of acquiring or not acquiring the music-sharing platform. You will have to create graphics and a slide deck summarizing your conclusion for a team of interviewers, who will be playing the role of Facebook executives. Good luck!
3 Tips for Data Science Case Interview
To learn how to answer data science case study interview questions, you need to practice. You may think you know everything you need to know because you have a high-powered degree. But the data science case study is a highly specialized process. Taking it slow is a surefire way to be outshined by your competitors and wind up looking unprepared. Consider case interview coaching.
Management Consulted provides expert training in every facet of the interview process, including the case study. Our proven techniques will help you refine the case interview skills you already have and develop new ones. You can also arrange to practice with friends and peers, if they have some degree of expertise. Have everyone generate their own insights and presentations from the same case interview practice cases, then present to one another. Seeing how other people work with the same material will help you increase your creativity. But be careful about taking too much advice from someone who may not be an expert on the case study data science interview.
TELL A STORY!
Many interviewers say that the most common downfall for data scientist applicants is that they fail to tell a narrative with their analysis. Think about it—if you’ve made it as far as the case study portion of the interview, then the company likely already trusts your technical expertise. What they want to know is whether you can translate your insights to your coworkers and higher-ups, who don’t have the same expertise you do.
LEARN TO EMPATHIZE!
Another major downfall for applicants is in a failure of communication skills. Communication is a huge component of what you’re being tested on. This starts with your ability to tell a story with your data, as noted above. It also includes your ability to sense what clients are looking for, as well as what the barriers are to making your insights understood and valuable. Don’t just rely on the numbers they give you, either. Do some research into the companies, products, and markets involved in your particular case study. This will help you imagine more creative solutions and better craft your insights.
If you’ve made it all the way to the case study portion of the data science interview process, then you’ve already accomplished a lot! What’s left is to prove that you’re a good fit. That proof isn’t just a demonstration of technical competence. It involves proving your ability to apply expertise to a specific environment. That means you need to communicate with people who don’t have your level of expertise. It also means you have to go beyond strict quantitative thinking and demonstrate your ability to apply that insight to real-world business concerns. That’s what the data science case study is all about.
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