Sabbatical December Report: My Year as a Data Scientist

This is a continuation of the series of my sabbatical reports. Here are the previous entries.

The skills needed to be a data scientist. I am tentatively done with my first project, and I have started my second (and last planned) project. I tentatively finished the first project in mid-December, but I am waiting until the New Year to present it to the (internal) client due to the fact that the end of the year is apparently busy for banks.

What I learned is that once can make huge gains by tuning hyperparameters. I started the modeling process by choosing an assortment of models. I started by using the default hyperparameters for each, and the initial results were terrible. However, after using some tools to find the best hyperparameters and then doing some manual experimentation, I actually ended up with better results than I thought I would able to get. It was like going from a score of 15% to 85%, just by getting the right hyperparameters.

How academia and business are different.

No report.

How will this experience influence my teaching? I am starting to think about how my new skills relate to the existing curriculum. It seems like there aren’t great fits. There aren’t any Mathematics courses that are relevant (I have some useful skills to help me with teaching statistics, but I am not actually using much actual statistics). Computer Science has a machine learning course, which I could fake my way through. However, I am sure that the Computer Science people are still much more qualified to teach this. We have three Data Analytics courses, and I think this is the closest match. The first course is on visualization, which is a skill I haven’t really developed yet. The second course seems to be a slightly more programming-heavy course, which might be a better fit. The third course is a capstone course, which seems to be the closest match to what I have learned—I haven’t learned a lot about any one subject (like machine learning), but I feel like I have gotten a lot of practice in solving very practical problems as they come up.

My feelings about being in industry. I was struggling with not having a winter break, but I got over that by mid-December. I am, however, grateful that the university schedule is what it is.

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5 Responses to “Sabbatical December Report: My Year as a Data Scientist”

  1. January Sabbatical Report: My Year as a Data Scientist | Solvable by Radicals Says:

    […] « Sabbatical December Report: My Year as a Data Scientist […]

  2. February Sabbatical Report: My Year as a Data Scientist | Solvable by Radicals Says:

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  3. March Sabbatical Report: My Year as a Data Scientist | Solvable by Radicals Says:

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  4. April Sabbatical Report: My Year as a Data Scientist | Solvable by Radicals Says:

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