Data Scientist

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Data Scientist

Currently we are looking to add a Data Scientist to the team who will bring his passion and expertise in Predictive Analysis.

FULL-TIME · AMSTERDAM

Lone Rooftop makes buildings intelligent.

Buildings are designed for people. So the ultimate intelligence that can contribute to the optimisation of a building’s performance and the people that use it is letting the building “know” where these people are. Lone Rooftop has developed a cloud platform that is calculating how many people, are where, at what moment in time.

Literally every process in a building can be optimised with this intelligence: from maximised utilisation driven by data, to time savings due to smart apps that help people find a vacant workspace that meets their needs. Elevators that are already there waiting for you as you walk towards them, and light and climate systems that adapt to the real time usage and therefore save energy consumption and increase comfort. The intelligent building is occupant oriented. It’s Lone Rooftop’s mission to make buildings truly efficient, hospitable and sustainable.

Your mission

  • You will apply advanced Machine Learning techniques to improve our positioning algorithm, which is the core of our product
  • You will be involved in the calibration of buildings with our platform, applying Regression Models and extracting accuracy measures
  • Depending on business needs, you may be involved in developing visual sensors using the most advanced computer vision techniques


About you

  • You have between 1-3 years of Data Science experience or 2-3 years as Data Analyst 
  • You are proficient in Python and Git; R is a Plus
  • You have a Statistics / Mathematics background 
  • Besides your academic experience you already have some commercial experience in the private sector, experience in a Startup is a big plus
  • You are passionate about reducing the carbon footprint and help the world become more sustainable 
  • It's a big plus if you have experience with computer vision or if you took part in Kaggle or other Data Science competitions.

Our offer to you

  • The opportunity to be part of a high-energy team at a ground breaking technology company with international ambition
  • The chance to have a real scale-up adventure with high risk, high reward mentality
  • You will have plenty of independence and responsibility as well as challenges to keep you learning
  • The possibility to make a difference in a company, and be valued for it
  • You will have lots of fun!

Lone Rooftop makes buildings intelligent.

Buildings are designed for people. So the ultimate intelligence that can contribute to the optimization of a building’s performance and the people that use it is letting the building “know” where these people are. Lone Rooftop has developed a cloud platform that is calculating how many people, are where, at what moment in time.

Literally every process in a building can be optimized with this intelligence: from maximized utilization driven by data, to time savings due to smart apps that help people find a vacant workspace that meets their needs. Elevators that are already there waiting for you as you walk towards them, and light and climate systems that adapt to the real time usage and therefore save energy consumption and increase comfort. The intelligent building is occupant oriented. It’s Lone Rooftop’s mission to make buildings truly efficient, hospitable and sustainable.

When we founded Lone Rooftop it was the perfect combination of an idealistic goal to improve the future, and a business opportunity. We got our first paying customers after only 3 months, and by now (2017) run our technology in 25 large office and educational buildings in The Netherlands, the U.K., while working on expanding our rapidly growing customer base, including several Fortune 500 companies.

Our technology has already resulted in some plans for new buildings being postponed, and further integrations with climate and energy systems mean that the remaining buildings will become greener. Our team has steadily grown, doubling about every 18 months in size, while we expect this to continue for the time being.