(this one produces center of world somewhere near Sao Tome and Principe)
Ever since starting a role at one of Google's sister companies under the Alphabet umbrella, I've had a number of people reach out to me requesting advice, suggestions, and guidance on interviewing and looking for tech jobs in general. Since I don't have time to respond to everyone, I thought I'd share my best advice in one doc. (Please note that I speak only on behalf of myself, and not on behalf of the company I work for.)
How should I prepare to interview at <company>?
This really depends on where you are in the job search process. If you're a year or more out, your focus should be on learning as much as you can at your current company or in school--no matter where you study or work, there is something you can gain from exploring the knowledge readily available to you from teachers and mentors in proximity to your current place in the world. Surround yourself with motivated people who care about learning just as much as you do and focus on personal growth and development.
Once you are a bit closer
Data Commons aims to simplify the process of data science by linking data from a variety of sources into one knowledge graph of information, simplifying the process of data cleaning for modeling. The purpose of this project was to make the knowledge graph more accessible to end users and easier for developers to add contributions.
In my proposal, I initially noted the following pain points in the Data Commons documentation:
- The directions for adding data sets in the 'Get Involved' section were short and unclear.
- The tutorials section only offered Python notebooks, with no reference to other Data Commons API wrappers.