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Data Scientist

Amninder Singh

I build geospatial ML pipelines

I design production-focused Earth observation and geospatial AI solutions for scalable remote sensing workflows.

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About

I’m a data scientist and geospatial ML engineer who turns Earth observation data into decisions people can actually use. I specialize in taking EO imagery from raw pixels to production-ready maps, models, and decision tools for agriculture and environmental management. Over the last several years, I’ve shipped work across research and industry: from graduate field campaigns in soil hydrology and salinity mapping, through postdoctoral remote sensing roles at UC Riverside and the USDA Salinity Lab, to production ML systems at Climate LLC (Bayer Crop Science). In those roles I’ve built modular, cloud-based pipelines for crop classification, soil salinity and moisture mapping, and land-use monitoring, with an emphasis on reproducibility, maintainability, and clear model performance. My PhD in Environmental Sciences (Soil & Water, UC Riverside) keeps me grounded in the real-world processes behind the pixels, and I bring that context into every model and workflow.

Education

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

Core Capabilities

  • Geospatial ML & EO

    End-to-end pipelines for landcover, biomass, and crop classification from optical/SAR imagery and GeoFM embeddings. Proficient in analyzing satellite imagery across platforms - Google Earth Engine, Descartes Labs, Apache Sedona, and libraries - Rasterio, xarray, GeoPandas, shapely etc.

  • ML Systems

    End-to-end pipelines, experiment tracking, model evaluation, CI/CD, MLflow, model monitoring, versioning.

  • Applied AI

    Computer vision, geospatial AI, multimodal feature engineering, segmentation, time-series modeling, transformers, foundation-model prototyping.

Other Skills Python Matlab R Soil and environmental sensor data acquisition systems Machine Learning Data visualization SQL Git Remote Sensing Deep Learning QGIS

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 – Nov 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 presenting the workflow to stakeholders.

Jan 2022 – Oct 2022

UC Riverside/USDA Salinity Lab

Post-Doctoral Scholar

The focus of my work was to study high-resolution soil-plant relationships. A particular focus was 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.

Tech Stack

Geospatial / Remote Sensing

  • GEE Google Earth Engine
  • Sedona Apache Sedona
  • Py Rasterio, Xarray, GeoPandas, Shapely
  • QGIS QGIS
  • EO Sentinel, Landsat, SAR, GeoFMs

Machine Learning / Data

  • Py Python - Pandas, Numpy
  • SK scikit-learn
  • PT PyTorch
  • TF TensorFlow

Cloud / MLOps

  • GCP Google Cloud - Vertex AI, Cloud Run, Cloud Storage
  • AWS AWS - S3, Lambda, Sagemaker
  • Airflow Apache Airflow
  • MLflow MLflow
  • DKR Docker
  • GHA GitHub Actions
  • Git Git

App / Web / Deployment

  • ST Streamlit
  • DJ Django
  • FA FastAPI

Featured Projects

Publications