In early 2017, “data scientist” was named the “Best job in America” for the second time in a row by the popular job site Glassdoor. Despite the surge in demand for data scientists in the tech and other industries, landing a job at a prestigious company is no easy feat. Based on our conversations with recruiters at top firms as well as senior data scientists in Switzerland, we have identified the four top skills that will get you hired:
Most employers require job candidates to know multiple programming languages and expect you to have a basic understanding of database querying languages too. As we’ve shown in another post, a majority of Swiss firms want you to know SQL, R and Python. For more technical roles you also have to master Java and/or C/C++. However, the required level of proficiency greatly depends on the seniority of the job: While senior roles require strong programming skills and work experience in the private sector, your willingness and enthusiasm to improve your programming and data analytic skills is often more important for junior roles.
Employers want you to have a strong technical background in statistics and data analysis. Indeed, acquiring these technical skills lays the foundation for effective on-the-job learning, and thus for becoming a successful data scientist. Most recruiters will ask you basic statistics questions at an early stage in the job interview process. If you don’t ace these questions, you’re out. According to Swiss recruiters and experienced data scientists, the following areas are most valuable to master:
Based on our own experience, we recommend that you focus on probabilities in particular. Most recruiters love to ask probability questions, since they can provide quick insight into your general thinking and problem solving skills. Be sure to polish your stats knowledge before you start interviewing.
Even if you’re the best programmer developing the most sophisticated data models, you won’t succeed as a data scientist unless you’re able to communicate your results in clear and simple terms. This holds true for more applied roles in particular, where visualizing and communicating results is at the core of the job. Frequently, you will have hundreds of interesting results but be required to filter out the most crucial ones and present them nicely: In applied roles, your job is to enable the management to make data-driven decisions without having to sift through large documents full of numbers. Be ready to explain complex statistics in simple yet accurate terms at your job interview!
Being a data enthusiast – and acting like one during the interview – is particularly important for junior positions. Recruiters want to hire people who love what they do and who are excited to learn new things. They want you to be an empirical, data-driven problem solver and decision-maker at heart: You love what the best data suggests are the facts, you hate alternative facts, and you make decisions accordingly. For some recruiters, being a data enthusiast is so important that they will prefer a candidate for whom working with data is like binge eating chocolate over a candidate with a more advanced technical background but less enthusiasm. There’s a good case to be made for this preference: Enthusiasm predicts long-term skill building, dedication, and ultimate success.
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