Rainforest QA is hiring a

Data Science Generalist

San Francisco, United States

Rainforest is a better way to do QA. We run functional tests against a crowd of humans. This means they are very fast and that customers can write tests in plain English, so there's no syntax or DSL to learn. Most of our paying customers run their Rainforest suite programatically as part of their deployment process. We're building Rainforest to replace Selenium and manual testing.

Here's a quick video: https://www.youtube.com/watch?v=iVFbigPTJBA

We run a lot of tests and we record everything that testers do to execute each test. Clicks, text entry, submission times, answers, screenshots… everything. Alongside that, we have fine-grained metrics on our testers, where they are from, what time they log into the system, how often they test with Rainforest. That's a lot of data and we could do so much more with it.

We're looking for someone to help us do that. Your role will be to use this data to improve the quality of the results we return to our customers, detect fraud, resolve disputes, generate tests automatically, create autonomous agents and many, many other things.

We're looking for someone with a strong background in data science, statistics and supervised learning, who stays on top of recent developments. You don't need to have used the latest neural net architecture, but you should know recent developments and be able to discuss where you think research is going in the next few years. You'll also need to write code to productize your work. Most importantly, you should be able to own your projects and see them through to improving the lives of our customers. This role would probably be perfect for academics who want to get into a small team that moves fast and ships software every day, but we do not require formal qualifications if you can show us some cool projects you've worked on.