Data Scientist

We're looking for an experienced Data Scientist to help us on an exciting new project based on our proprietary clickstream data. We collect tens of millions of events per month, from tens of thousands of users across the world.

Since its launch in 2018, Gener8 has been at the forefront of the “open data” movement: the belief that people should be able to control and be rewarded from their own data. Gener8’s consumer products include a web browser, browser extension, IOS and Android apps. Our products enable people to transparently and willingly share their data with Gener8, whilst preserving their privacy, so that we can create value from it for them.

We are growing fast. With tens of thousands new app downloads every month. Every month our desktop browser racks up the equivalent of 250 yrs in time spent browsing on it. As you can imagine, we have huge amounts of proprietary data which we can create value from.

Gener8 was named ‘Disruptor of the year’ in 2022 by the Great British Entrepreneur Awards. Our investors include 3 Dragons fromas well as personalities such as the rap star Tinie Tempah, former football manager Harry Redknapp and cricketer Chris Gayle to name a few. In 2023 we met with the Prime Minister at Downing street and were invited to become a member of the Government’s new “Smart Data Council”, shaping the future of data legislation in the UK. We also regularly engage with European legislators on the Digital Markets Act which empowers users to control and earn from their data.

The first part of the project will involve modelling our raw clickstream data to make it nationally representative of the UK and US, where we already have relevant national census data.

The second part will be analysing this dataset for behavioural changes amongst several cohorts of users, to measure how it has changed over time (~1yr) and understand this in greater detail.

There is also the opportunity to include our other datasets in this analysis, such as in-app usage.

As well as executing the modelling and analysis we'll be looking to learn from you what the best approach is and questions to ask are, as we discover more through the project.

The final output will firstly be a presentation given to senior business stakeholders, technical experts and other data scientists as well as an accompanying written report.

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• Nat Rep modelling
  
• Analysing large clickstream (pageview) datasets
  
• Python and or R
  
• SQL
  

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• Primary dataset: ~200GB, ~360m rows, ~30 columns
  
• Dialect: BigQuery - we can provide experienced in-house technical support with complex queries