Recycleye | Data Scientist | London | 2-3x/week ONSITE | Mid to Senior level
Recycleye and CP Group build recycling plants, and are forming a new team to provide data analytics and optimisation to recycling facility operators. There are optical sorters, AI powered airjets, AI robots and many different types of machines in a waste facility. The waste is constantly varying and the plant can be configured in thousands of ways to sort the material. This team will be collecting this data using different sensors and cameras.
We're looking for a data scientist with experience in deep analytics and statistical modelling to understand and visualise the data, and then and model the plant to spot issues before they impact operations, and identify optimistions that make a real difference. We use Clickhouse and Python or Go.
This might be a problem, but if you're careful to make use of transparency, axis scaling and random jitter (for integer or categorical values), the occlusion issue can be overcome.
For me the readability of tidyverse code is crucial. I like pandas and use it daily, but often it requires deciphering to understand what is happening, especially regarding indexing. But tidyverse code can be easily read, and that has been a big help in enabling collaberation amongst our data team.
Do you have a forum or suggestions tool at all? Fivetran has been amazing for our new datawarehouse and we're very pleased with the service, but there are a few little (non-bug) things that would have made it even easier.
Beyond Compare has a tabular data mode, where you set the key columns and it presents the differences in a nice interface. Works well for me.
http://www.scootersoftware.com
They're weren't claiming that when you searched bing, they did a google search immediately in the background. Rather, they claim that they were collecting google's ranking and using it in their own ranking algorithms. They wouldn't have ever have collected data on hiybbprqag without their previous actions.
Recycleye and CP Group build recycling plants, and are forming a new team to provide data analytics and optimisation to recycling facility operators. There are optical sorters, AI powered airjets, AI robots and many different types of machines in a waste facility. The waste is constantly varying and the plant can be configured in thousands of ways to sort the material. This team will be collecting this data using different sensors and cameras.
We're looking for a data scientist with experience in deep analytics and statistical modelling to understand and visualise the data, and then and model the plant to spot issues before they impact operations, and identify optimistions that make a real difference. We use Clickhouse and Python or Go.
Any questions, feel free to email me at [email protected]