Because I love baby elephants
Sometime ago I was asked to write up answer to these questions. Thought I would be here also.
What advice would you give to aspiring data scientists?
Data science is a big field with diverse roles. Some focus on making better business decisions, while some of us spend our days makingnew products. This diversity is driven by the company, the industry, and the team you will join. Talk to as many data scientists as you can, because these early choices will dictate what your days are like. There is a place for almost every type of data scientist. It’s important to figure out which one you want to be.
Where is a good place to start for them to get hands-on experience?
Look around; there are interesting questions everywhere. Kaggle provides you with premade questions, curated data, and a predefined gold standard of accuracy. Data science is never that simple. Don’t limit yourself to questions that others have asked. Look around, think creatively, ask questions about your interests. Define your questions, find your data, and define what “good” should look like. Then write about it.
What resources did you use to learn?
I worked in academia as a computational physicist and biologist for 15 years. The questions within these areas are domain-rich and mathematically complex. Often, we do not have enough data (or the data is too noisy) to answer the questions we pose. This has the benefit of forcing you to think carefully about your hypotheses and sit with a problem before starting any coding. No one should spend a year trying to answer the wrong question.
What is the best advice you’ve ever been given going into the data science industry?
I was told that I would have access to data that no one in the world has. They were right.
