At Woven Plant, we are developing technologies that will benefit all of humankind. That's why we are working every day to make our workforce as diverse as possible: the more variety our team has in our experience, interest, and backgrounds, the more likely we are to create truly great technologies. We also believe that our society as a whole benefits when we reach out to include a greater number of previously under-represented employees. To help us deliver on these promises, we encourage you to share your gender, ethnicity, race, veteran status, and disability. For government reporting purposes, we ask candidates to respond to the below self-identification survey.
What is it like to be a research scientist at Google? originally appeared on Quora: the knowledge sharing network where compelling questions are answered by people with unique insights. What is it like to be a research scientist at Google? Google probably has the highest concentration of talent in Computer Science (especially in some subfields like Machine Learning) of any institution on the planet, and in general employs more CS PhDs than any university. This means that there are people around who wrote the book on whatever it is you are interested in. And usually they would be happy to answer any question you may have. All the cutting edge research is presented internally, usually before it makes it out.
Alice decides to do some quick analysis on the trends using Kaggle Data Science survey to see what backgrounds do the current Data Science practitioners have. A majority of data scientists have college degrees, infact a majority of them have a Masters degree. So Alice would do well to go to college. But Alice is also curious of the importance of getting a degree if she wants her dream job in her dream country. Let's look at those patterns.
About us100ms is building a Platform-as-a-Service for developers integrating video-conferencing experiences into their apps. Our SDKs enable developers to add gold standard audio-video quality conferencing with much faster shipping times. We are a team uniquely placed to work on this problem. We have built world-record scale live video infrastructure powering billions of live video minutes in a day. We are a remote-first global team with engineers who've built video infrastructure at Facebook and Hotstar.
Although they certainly work together amicably and enjoy some overlap concerning expertise and experience, the two roles serve quite different purposes. Essentially, we are differentiating between Scientists who seek to understand the science behind their work, and Engineers who seek to build something that can be accessed by others. Both roles are extremely important, and at some companies, are interchangeable -- for example, Data Scientists at certain organizations may carry out the work of a Machine Learning engineer and vice versa. To make the distinction clear, I'll split the differences into 3 categories; 1) Responsibilities 2) Expertise 3) Salary Expectations. Data Scientists follow the Data Science Process, which may also be referred to as Blitzstein & Pfister workflow.