LinkedIn presentation at Careers in Math

Sara Smoot Gerrard spoke today about data science and machine learning. She discussed a lot of the problems involved with the idea of "data science", something that hasn't been clearly defined to a lot of people. When companies want to "provide value" to their customers, they often don't know what they mean. It's a data scientist's job to refine that goal and decide what data can be used to improve the value of the product.

It is often difficult to decide what features to use in a model, when there could be billions of features available and not all of them matter. For example, for discovering groups on LinkedIn they found it was better to limit the product to only give suggestions of groups that already had people connected to the user.

To do well in data science, it's important to have the mathematical and statistical skills as well as solid coding ability. Without either one, a data scientist will not have the ability to conceptualize a solution and implement it so it can be deployed.

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