United States onlyTeam: Location: Remote Who We Are: We are a climate tech company committed to reversing climate change. How do we reach this lofty goal? By disrupting the agriculture industry!
Founded by globally-recognized innovators in science and ag technology, Regrow is unlocking the power and profitability of resilient agriculture across the supply chain — from growers to global food brands. Regrow combines best-in-class agronomy, soil and carbon modeling, and innovative data collection to deliver customized, site-specific and scalable solutions to the agri-food industry.
Our customers are frontrunners in agri-food and agtech, 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 Microsoft's Venture Fund, Cargill, The Grantham Environmental Trust (NCO), AJAX Strategies, 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 200 million acres of land in over 45 countries. 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 FosterAs a Geospatial Data Scientist at Regrow, you will create the data products behind our agricultural monitoring, reporting, and verification tools. Using your expertise in statistical analysis and data visualization, you will drive quality assessment, visualization, and reporting on the accuracy of the data Regrow uses to identify regenerative agricultural practices globally, allowing growers and the companies that depend on them to build more sustainable supply chains.
What You'll do
- Leverage your statistical knowledge to clean, summarize, and visualize various field level data sets including internal datasets, government surveys, and other 3rd party agricultural survey data.
- Work with the Data Science and Data Engineering teams to assess the accuracy and quality of landscape scale data products (crop type, agricultural practice adoption, etc).
- Source reference data describing regional cropping and agricultural practices in the US, Europe, Brazil, and beyond.
- Oversee the collection of ground truth data collection for crop type, agricultural practices, and land use change.
- Apply best practices for sourcing, normalizing, and merging data from multiple sources (eg field surveys, self reported data, etc) for use in model training and assessment.
Qualifications
- Bachelor degree or equivalent experience in Earth Science, Remote Sensing, Computer Science, Statistics, or a related field.
- Experience using statistical techniques to evaluate tabular agricultural, forestry, or other natural resources data products.
- Strong SQL programming skills, preferably experience with BigQuery and Postgres.
- Experience creating data reports and visualizations using business intelligence tools like Looker or Tableau.
- Python programming skills, including scientific and data visualization libraries (pandas, NumPy, SciPy, PyViz, Jupyter, etc).
- Excellent English language technical writing and presentation skills.
Desirable Skills: (bonus if you have them)
- Ability to apply standard software development processes using Git and clearly document results.
- Familiarity with spatial statistics, remote sensing, and/or agronomy.
While it may go without saying once you see the diversity on our current team, we encourage diversity on our team at all levels of the company. We are committed to fostering a diverse, inclusive environment and to encourage these values in everyone on our team. We provide an environment of mutual respect where opportunities are available without regard to race, color, religion, sex, pregnancy (including childbirth, lactation and related medical conditions), national origin, age, physical and mental disability, marital status, sexual orientation, gender identity, gender expression, genetic information (including characteristics and testing), military and veteran status, and any other characteristic protected by applicable law. We believe that diversity and inclusion for people from all walks of life is key to our success as a company.
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