Company Overview:
As an established real estate firm, we specialize in the acquisition of vacant land parcels. Our extensive database consists of approximately 50,000 land parcels, with some inaccuracies due to government classifications. Our commitment to accuracy and efficiency has driven us to seek an advanced solution to rectify these discrepancies.
Role Overview:
We are in search of a proficient Data Scientist with expertise in geospatial analysis and machine learning. The candidate will be tasked with harnessing existing open-source building detection models, optimizing them to suit our unique requirements.
Responsibilities:
Evaluate and select an appropriate open-source building detection model.
Fine-tune the selected model to ensure maximum accuracy for our specific dataset.
Design and implement a system that can process batch inputs of thousands of land parcels.
Generate precise outputs indicating the presence of a building on each parcel, accompanied by the building's estimated square footage.
Desired Outcomes:
By the culmination of this project, we aim to have an efficient model in place that can accurately sift through our database, rectifying misclassifications and ensuring that we are well-informed about the true nature of each land parcel.
Qualifications:
Experience in geospatial data analysis and processing.
Proficient in machine learning, particularly in the domain of image recognition.
Familiarity with open-source building detection models and tools.
Strong problem-solving skills and an analytical mindset.
Interested candidates are encouraged to showcase previous projects or experiences that align closely with the requirements stated. Join us in our endeavor to blend real estate with cutting-edge technology.
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