Geospatial Data Scientist

Kooling
London
6 months ago
Applications closed

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The Company Kooling mission is to make the worldscities more efficient, safer, greener and beautiful. We are backedby private investors and the UK Government via its VC investmentarm InnovateUK and have FTSE100 companies, European listedcompanies, world class Universities and worlds leading CityAdministrations as Customers. The Job This role is for anentrepreneurial and experienced candidate who is seeking to join asmall team leading large and prestigious projects. You will leadthe development and ongoing maintenance of our modal detectiontechnology. You will spend your time with a small group of leadingtech professionals with a passion for their job and a personaldrive to join a growth adventure and make things happen. Activitiespart of your job: Continuous improvement of our leading proprietarymodal detection algorithms Preparation and maintenance ofprofessional Documentation Assess and implement applicablescientific research findings Qualities we value Entrepreneurialattitude Pride for a job well done Clarity in communicationPersonability Tenacity Eye for details Willingness to learn CourageCamaraderie Technical Skills Strong experience in applyingheuristics and statistical methods to time series in the analysisgeospatial data Experience and interest in GPS time series andother sensors data Experience in improving and designing geospatialdata-based algorithms Expertise in at least one keyprogramming/scripting language (Python/C++/other) Capable toidentify and implement key scientific research into algorithms tocreating value for Customers Design and deployment of ML modelsfrom inception to completion, covering problem formulation,experimentation, iteration, and eventual publication or productintegration Qualifications BSc/MSc in Computer Science or similarfield is a strong advantage Fluent Professional English BenefitsOpportunity to join the company full time upon successful part timeengagement Highly competitive performance-based incentives LocationHybrid or Remote

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