Senior Spatial Statistician

Senior Spatial Statistician Team: ScienceLocation: Remote​​
​​Who We Are
We are a climate tech company committed to reversing climate change. How do we reach this lofty goal? By ushering the agriculture industry into the new era!
Founded by globally recognized innovators in science and ag technology, Regrow is unlocking the power and profitability of resilient agriculture across the supply chain — supporting industry leaders, from growers to global food brands. Regrow combines best-in-class agronomy, soil and carbon modeling, remote sensing and AI to deliver customized, site-specific, scalable solutions to the agri-food industry.
Our customers are frontrunners in agri-food and agtech (Cargill, General Mills, Nutrien, Unilever), ranging from global market operators, project developers, global food brands, and independent farmers. We help partners measure their impact on the environment, model and implement changes that will be environmentally and financially sustainable, and track partners’ progress against sustainability goals. 
We're backed by leading investors, such as Galvanize Climate Solutions, Microsoft's Venture Fund, Cargill, The Grantham Environmental Trust (NCO), TIME Ventures, Main Sequence Ventures (MSEQ), and more, all of whom believe in our vision to change the world through resilient agriculture.
Our Mission:Agriculture has the power to reverse climate change. We believe science and technology can help us get there. Our goal is to use farmland to cool the earth.
We are currently monitoring 1.2B acres of land (10% of global arable land). This year alone, with just one project, our carbon emissions reductions are equivalent to taking 17,000 cars off the road! We are already on our way to a more sustainable planet.
Growth You’ll Foster

As a Spatial Statistician at Regrow, you will evaluate the quality and accuracy of the data products behind our agricultural  monitoring, reporting, and verification tools. Using your expertise in statistical analysis and machine learning, you will develop the frameworks and tools Regrow uses to reliably identify regenerative agricultural practices globally, allowing growers and the companies that depend on them to build more sustainable supply chains. 
 

What you will do:

• Design and implement framework for assessing accuracy and quality of landscape scale data products (crop type, agricultural practice adoption, etc)
• Create protocols for crop type, agricultural practice, and land use change ground truth data collection. Methods to include field visits, imagery interpretation and annotation, farm machine generated data, crowdsourcing, etc.
• Identify, develop, and apply methods to normalize and combine data from multiple sources (eg field surveys, self reported data, etc).
• Develop automated data validation and review frameworks for machine learning based data products. 
• Identify and integrate relevant remote sensing and other spatial datasets for model development and improvement, including multispectral and SAR satellite imagery, weather and soil data, in-field measurements, and farm machinery datasets.
• Leverage familiarity with current best practices in remote sensing science and statistics to drive innovation across the Data Science organization.
• Provide domain expertise to cross-functional discussions about product design, improvement, and implementation. Advocate for practical, relevant, and scientifically valid solutions.
• Contribute across the full product life-cycle: conduct R&D on potential focus areas, develop proof of concept data products for new offerings, and iterate on existing models to improve core products. 
• Mentor junior members of the team, facilitating the development of technical expertise and science communication skills.

Qualifications:

• Advanced degree or equivalent experience in Earth Science, Remote Sensing, Computer Science, Statistics, or a related field.
• Experience using statistical and machine learning expertise to evaluate remote sensing based data products datasets. 
• Strong Python programming skills, including scientific and machine learning libraries (NumPy, SciPy, SKLearn, etc).
• Ability to apply standard software development processes and clearly document results.
• Demonstrated ability to utilize remote sensing imagery for large-scale monitoring and/or modeling of agriculture and/or natural ecosystems.
• Excellent English language presentation and communication skills

Desirable Skills: (bonus if you have them):

• Experience working on agricultural applications in South America and/or Europe
• Familiarity with Google Earth Engine or other cloud-based satellite imagery analysis environment

Envision Yourself Here
Does this sound like your dream job? If so, go ahead and apply for the position and we