Jr ML Data Scientist
Remote - US
Regrow Ag Inc.
Measure, report, and reduce on-farm emissions with Regrow's Agriculture Resilience Platform. See how to cut scope 3 emissions and hit your net zero goals.Team: 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 ML 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 select and apply model evaluation metrics across Regrow’s suite of models and data products. Analyze model performance and identify areas for improvement.
- Develop and implement data pipelines for efficient data ingestion and processing. Use these pipelines to create high-quality training and validation data for model development and evaluation.
- 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 ground truth and derived data for model training and validation. Data can include cropping and agricultural practices, irrigation timing, and biophysical data (eg crop residue cover).
- Train, evaluate, and optimize ML/DL models to achieve desired performance metrics. Communicate findings effectively to technical and non-technical audiences.
Qualifications
- Advanced degree or equivalent experience in Earth Science, Remote Sensing, Computer Science, Statistics, or a related field.
- Experience building statistical, machine learning, and/or simulation models using remote sensing datasets.
- Strong Python programming skills, including scientific and machine learning libraries (NumPy, SciPy, SKLearn, TensorFlow, etc).
- Demonstrated ability to apply remote sensing imagery to large-scale monitoring and/or modeling in agriculture and/or natural ecosystems.
- Experience in using deep learning frameworks such as PyTorch, Keras, or TensorFlow.
- 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.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Computer Science Data pipelines Data visualization Deep Learning Engineering Git Keras Machine Learning ML models Model training NumPy Pipelines Python PyTorch Scikit-learn SciPy Statistics TensorFlow Testing
Perks/benefits: Career development Startup environment
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