Hello there, Thanks for stopping by!

My name is Amninder Singh.
And I am a Data Scientist


More About Me

With a growing population, water shortages, and climate change impacts, it is clear that we need to keep working to find solutions that make agriculture more efficient. The efficiencies enabled by the advancement of digital technologies can help us get more out of agriculture while conserving our natural resources. I am a researcher passionate about using earth observatory data, geophysical measurements, and machine learning approaches to address these challenges. I received my Ph.D. in Environmental Sciences (soil & water) from UCR and then worked as a post-doctoral researcher with Scudiero Lab at the USDA Salinity Lab.


2018 - 2021

University of California, Riverside

Ph.D., Environmental Sciences (Soil &Water)

2015 - 2017

California State University (CSU), Fresno

MS, Plant Science

2011 - 2015

Punjab Agricultural University, India

BS, Agriculture


  • Python

    I have worked on various machine learning projects using agricultural datasets. Experience working with libraries such as TensorFlow, pandas, NumPy, matplotlib, seaborn, etc.

  • Geospatial data analysis

    Proficient in analyzing satellite/drone imagery using platforms like ArcGIS, QGIS, and Google Earth Engine. Python libraries: Geopandas, Rasterio, xarray

  • Work Experience.

    Nov 2023 - present

    Climate LLC

    Data Scientist

    Working as a Data Scientist, Remote Sensing. Climate LLC (DFS) is the digital farming arm of Bayer Crop Science.

    Nov 2022 - November 2023

    Climate LLC

    Geospatial Data Scientist (Contract)

    I worked as a contractor with the Data Insights Geospatial and Remote Sensing team. Responsible for fulfilling requests for geospatial data analysis from various teams and creating and presenting the workflow to stakeholders.

    Jan 2022 - Oct 2022

    UC Riverside/USDA Salinity Lab

    Post-Doctoral Scholar

    The focus of my work is to study high-resolution soil-plant relationships. A particular focus will be on the estimation of soil moisture by combining public and private soil moisture ground measurements, remote sensing, and other datasets with machine learning methods

    Jan 2018 - Dec 2021

    UC Riverside

    Graduate Student Researcher

    Dissertation: 'Advancing Urban Landscape Irrigation Management using Smart Controllers and Machine Learning-Based Models'. Worked on a variety of projects related to irrigation and water management using different approaches, such as advanced data acquisition, machine learning, remote sensing, and GIS & GPS technologies. I was responsible for aggregating & statistically analyzing large agricultural datasets using Python, R or MATLAB

    Aug 2015 - Dec 2017

    CSU, Fresno

    Graduate Research Assistant

    Thesis: 'Use of EM-38 soil surveys in forage fields at a saline drainage water reuse site to calibrate a hydro-salinity model for decision support.' I was responsible for conducting soil salinity mapping using electromagnetic sensing platforms and analyzing spatial data.


    Soil Moisture Estimation of Agricultural Fields using Remote Sensing

    Autonomous landscape water conservation strategies using smart irrigation controllers

    Temperature-based empirical and ML ET models

    Artificial Neural Network (ANN) based Pedotransfer functions

    Electromagnetic Induction (EM-38) for mapping soil salinity


    Contact Me


    Los Angeles, CA