Requirements:**Managers are seeking local candidates. They prefer for this candidate to work onsite in the Mountainview CA **

Qualifications

• Master's Degree in Computer Science/Electrical Engineering, Math, or related field.
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• Master’s with at least 1-2 years of experience; Strong software engineering practices in Python with machine learning experience in a production setting.
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• In-depth technical knowledge and skills including geo-database design and spatial relationships.
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• Thorough understanding of (geo-)statistics and data extraction and analysis
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• Strong Machine Learning and/or statistics background
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• Experience using Python or R in a production context.
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• Experience using PySpark and Pandas
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• Experience collaborating on projects using a distributed version control system such as Git or Mercurial.
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• Experience developing performant, interactive visualizations of large-scale geospatial data.
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• AWS and Databricks experience
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• Familiar with containers
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• Excellent oral and written communication skills, skilled in communicating technical topics to non-technical audiences.
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Responsibilities

As a Geospatial Data Scientist, you will be the go-to person for geospatial data analysis. you will play a crucial role in supporting our data-driven decision-making processes. Your main responsibilities will include collecting, analyzing, and interpreting large complex geo-datasets, developing predictive models and algorithms, and presenting insights to key stakeholders.  Responsibilities and required qualifications are as follows:

• Collect and pre-preprocess geospatial data to prepare for analysis.
• Lead the application of advanced analytical methods, including machine learning and statistical techniques, to develop consumer-centric insights.
• Explore and evaluate different data storage and management techniques specifically designed for geospatial data for efficient access.
• Create a data workflow from data acquisition to trends and insights generation.
• Produce high quality tested code that enables large scale research and can be transferred to physical vehicles or to the cloud infrastructure deployed in the real world.
• Stay up to date on the state-of-the-art in machine learning and data analysis ideas and software, in collaboration with our Researchers.
• Coding, proof-of-concept (POC) and demo applications using our platforms.
• Work in a multidisciplinary team and collaborate with other teams across the research lab.