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Senior Spatial Statistician

Regrow Ag

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Posted over 30 days ago...

Expired

Join our mission-driven climate tech company as a Senior Spatial Statistician and harness the power of resilient agriculture to reverse climate change

Overview

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£120000

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Remote - US

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100% Remote- Worldwide

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Expires at anytime

Organisation summary: Regrow is at the forefront of climate tech innovation, dedicated to reversing climate change through resilient agriculture. With a focus on the agriculture industry, we utilize advanced agronomy, soil and carbon modeling, remote sensing, and AI to deliver scalable solutions. Our work supports industry leaders and independent farmers alike, enabling them to measure environmental impact and pursue sustainable practices. Our monitoring covers an astounding 1.2 billion acres, contributing significantly to carbon emissions reduction and backed by top investors who share our vision of using farmland to cool the earth.

  • Role Summary:
    • Lead the evaluation of data product quality and accuracy for agricultural monitoring tools.
    • Design frameworks for assessing landscape scale data products.
    • Create protocols for ground truth data collection on agricultural practices.
    • Develop best practices for data sourcing, normalization, and merging.
    • Integrate remote sensing and spatial datasets for model development.
    • Drive innovation within the Data Science organization through remote sensing and statistics.
    • Engage in cross-functional discussions on product design and implementation.
    • Contribute to the full product life-cycle, from R&D to model iteration.
    • Mentor junior team members, enhancing their technical and communication skills.
  • Role Requirements:
    • An advanced degree or equivalent in Earth Science, Remote Sensing, Computer Science, Statistics, or related fields.
    • Experience with statistical and machine learning for remote sensing data evaluation.
    • Proficiency in Python and relevant scientific and machine learning libraries.
    • Experience with large-scale remote sensing imagery in agriculture or natural ecosystems.
    • Strong English language communication skills.
    • Desirable: Experience in agricultural monitoring and familiarity with cloud-based satellite imagery analysis environments like Google Earth Engine.
  • Application Process Details:
    • Apply for the position to embark on your dream job.
    • We value diversity and encourage applicants from all backgrounds to join our inclusive team.

Spatial Statistician 

Team: Science

Location: 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 Senior 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 ground truth data collection and creation protocols for crop type, agricultural practice, and land use change. Methods to include field visits, imagery interpretation and annotation, farm machine generated data, crowdsourcing, etc. Develop and drive application of 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. 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 monitoring evaluation protocols in multiple countries 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’ll be in touch. We appreciate your interest in Regrow. 

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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