by Angela Guess
Michael Li recently wrote in the Harvard Business Review, “If you’re looking to hire a data scientist to join your company, you’re not alone. At The Data Incubator, we work with hundreds of companies that are looking to find data scientists from our Fellowship Program. In our experience, candidates usually come from one of two disciplines: computations or statistics. Candidates with a strong science or math background usually have had rigorous statistical training in distinguishing between signal and noise and can tell when they are ‘overfitting’ a complex model. Those with a computer science background frequently have the software engineering chops to handle large amounts of data by taking advantage of parallel and distributed computing.”
Li goes on, “While all data scientists need to be functional in both, we’ve found that people coming from each of these backgrounds have quite different strengths and weaknesses. So which type of background should you look for when hiring? That will depend on your business — and whether you’re hiring for a digital or non-digital department.”
He continues, “Digital departments. Think about the departments in the digital economy that have a regular profusion of data, generated from mobile, tablet, laptop, or desktop sources. Mobile apps, e-commerce, wearables, and digital advertising are just a few companies that fall into this category. When data is plentiful, analytics often benefits from the unreasonable effectiveness of data — the idea that as we are able to learn from more data, we are able to achieve increasingly accurate models. Doing so certainly requires a deep knowledge of statistics. But a strong computational background is needed even more. These companies often benefit from having data scientists with software engineering backgrounds who can quickly build the systems that learn new trends in real time.”
photo credit: Flickr/ katerha