Remote Sensing Data Scientist

Overview

We are seeking a highly skilled Remote Sensing Data Scientist with deep expertise in remote sensing principles, machine learning, deep learning, geospatial analytics, and image processing to join our dynamic team. The ideal candidate has a proven track record working with remote sensing data (satellite, aerial imagery) and can translate imagery into actionable insights through advanced modeling techniques.

• Apply foundations of remote sensing and advanced techniques in image analysis, geospatial analytics, machine learning, and deep learning to extract insights from complex imagery datasets (e.g., multispectral, hyperspectral, SAR).
• Build, validate, and operationalize predictive and prescriptive analytics solutions that enhance efficiency, reliability, and decision making across agricultural operations.
• Design and implement pipelines for imagery ingestion, preprocessing, feature extraction, and model deployment at scale.
• Write comprehensive model documentation, including problem framing, data requirements, modeling approach, validation, and operationalization.
• Adhere to data science best practices—peer review, code review, reproducibility, and version control.
• Partner closely with agronomic scientists, biologists, field operations teams, and digital product teams to co develop remote sensing solutions aligned with business needs.
• Collaborate with customer global Data Science community to leverage shared tools, platforms, and modeling frameworks.
• Communicate complex technical concepts, model performance, and insights to stakeholders clearly and effectively.

• Agriculture & Agronomy Background:
  Foundational understanding of agricultural systems, crop development, field operations, and agronomic principles. Ability to contextualize remote sensing insights within agronomic workflows (e.g., crop health diagnostics, field variability, environmental influences). Experience collaborating with agronomists or applying remote sensing to real world agricultural challenges is highly beneficial.
• Cloud & Engineering
  
  Skills:
  
  Experience with cloud platforms (AWS, Azure, or GCP) for scalable data processing and deployment.
• Programming
  
  Skills:
  
  Proficiency in Python and common ML/DL libraries (Tensor Flow, PyTorch, OpenCV, scikit learn). Experience with SQL for querying, transforming, and managing structured datasets. Strong coding discipline, including maintainable code, testing, version control (Git Hub), and reproducible workflows. Familiary with AI assisted coding tools and technologies for rapid prototyping.
• Soft Skills:
  
  High sense of ownership, curiosity, and motivation to deliver impactful analytic. Ability to explain technical findings to non technical audiences. Strong collaboration and communication skills across diverse functional teams.

• Imagery & Remote Sensing Expertise:
  Hands-on experience working with remote sensing datasets. Strong knowledge of image processing techniques (e.g., atmospheric correction, orthorectification, segmentation, and feature extraction). Experience with geospatial tools (e.g., GDAL, Rasterio, Geo Pandas) and working with spatial data formats.
• Machine Learning & Deep Learning:
  Proficiency in applying ML/DL methods to imagery: CNNs, semantic segmentation, object detection, time series modeling, usage of foundational models. Strong understanding of statistical concepts, model evaluation, and uncertainty quantification.

• Ph.D. or M.S. (with 4+ years of experience) in Remote Sensing, Geospatial Science, Data Science, Agronomy, Imagery & Robotics, or related fields.

US Tech Solutions is a global staff augmentation firm providing a wide range of talent on-demand and total workforce solutions. To know more about US Tech Solutions, please visit

US Tech Solutions is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.