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Remote Agronomy Research Jobs (NOW HIRING)

... systems, and/or agronomic problems. * Strong foundation in Python programming in a cloud ... S. in Computer Science, Computational Physics, Operations Research, Geospatial Sciences, Remote ...

BRT acts as a research and development flywheel, building not only new products but also new ... Remote in the United States * Visa sponsorship : Open to visa sponsorship. Job Responsibilities A ...

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Remote Agronomy Research information

What is remote agronomy research?

Remote agronomy research involves studying crop production, soil health, and agricultural practices using digital tools and technology from a distance. Researchers analyze data collected by drones, satellites, sensors, or remote field monitoring systems to make recommendations without being physically present in the field. This approach enables efficient data collection over large areas, supports precision agriculture, and allows for real-time decision-making to improve crop yields and sustainability.

What is the difference between Remote Agronomy Research vs Remote Soil Scientist?

AspectRemote Agronomy ResearchRemote Soil Scientist
CredentialsBachelor's or higher in Agronomy, Plant Science, or related fieldsBachelor's or higher in Soil Science, Geology, or related fields
Work EnvironmentRemote research projects, data analysis, field trial coordinationRemote soil analysis, sample interpretation, environmental assessment
Industry UsageResearch institutions, agricultural companies, universitiesEnvironmental agencies, consulting firms, agricultural businesses

Remote Agronomy Research and Remote Soil Scientist roles share similar credentials and work environments, focusing on agricultural and environmental research. However, Remote Agronomy Research emphasizes crop and plant studies, while Remote Soil Scientists specialize in soil analysis and environmental assessments. Both roles are vital in advancing sustainable agriculture and environmental practices remotely.

What are the key skills and qualifications needed to thrive in Remote Agronomy Research, and why are they important?

To thrive in Remote Agronomy Research, you need a strong background in plant science, soil science, and data analysis, typically supported by a degree in agronomy, agriculture, or a related field. Familiarity with remote sensing technologies, GIS software, and statistical analysis tools is essential for collecting and interpreting agricultural data. Strong problem-solving skills, attention to detail, and effective communication are crucial for collaborating with teams and presenting research findings. These skills ensure accurate research, innovative solutions, and successful application of agronomic practices in remote settings.

What are some common challenges faced by professionals in remote agronomy research, and how can they be addressed?

Professionals in remote agronomy research often encounter challenges such as ensuring accurate data collection from afar, maintaining effective communication with field teams, and managing technology used for remote monitoring. Establishing robust data protocols, utilizing reliable digital tools, and scheduling regular virtual check-ins with on-site staff can help overcome these obstacles. Building strong collaborative relationships and staying up-to-date on remote sensing technologies are also key to successfully conducting research and driving impactful results.
More about Remote Agronomy Research jobs
What cities are hiring for Remote Agronomy Research jobs? Cities with the most Remote Agronomy Research job openings:
What are the most commonly searched types of Agronomy Research jobs? The most popular types of Agronomy Research jobs are:
What states have the most Remote Agronomy Research jobs? States with the most job openings for Remote Agronomy Research jobs include:
What job categories do people searching Remote Agronomy Research jobs look for? The top searched job categories for Remote Agronomy Research jobs are:
Infographic showing various Remote Agronomy Research job openings in the United States as of June 2026, with employment types broken down into 86% Full Time, 7% Part Time, and 7% Contract. Highlights an 7% In-person, and 93% Remote job distribution.
Data Science Specialist

Data Science Specialist

Adidev Technologies Inc

Manhattan, NY • Remote

Full-time

Posted 15 days ago


Job description

Adidev Technologies Inc 

www.adidevtechnologies.com

URGENT HIRE - HIRING PROCESS - 24-48 HOURS!

Adidev Technologies is seeking 1-2 yrs of relevant experience in Data Science. A project can last anywhere from 6 months to 18 months. Salary varies depending on experience, and we are in search of candidates looking to start as soon as possible. Excellent written and oral communication are required as is the ability to work well in a team environment.

If you are looking for a new challenge and are ready to make an impact on a growing team, then this will be a perfect fit. As a Data Scientist/Data Science Specialist for Adidev Technologies Inc., you will be enhancing and debugging large-scale applications for one of our well-known clients.

Adidev Technologies is a growing software consulting company that is constantly expanding. As we are working with renowned clients and ready to take on new ones, we are seeking brilliant software engineers. Not only do we offer a great team to work with, but we also offer you an opportunity to make an immediate impact and get rewarded accordingly

 

Job Description

  • Demonstrated experience using machine learning, deep learning, statistical methodology, and simulation/optimization modeling in geospatial, network topography, recommendation systems, environmental systems, and/or agronomic problems.
  • Strong foundation in Python programming in a cloud environment.
  • Strong quantitative abilities, distinctive problem-solving, and excellent analysis skills
  • Expertise in data wrangling using SQL,
  • Practical knowledge and experience with cloud-computing systems and platforms, including the routine deployment of pipelines through Kubernetes
  • Fluency in querying/extracting/aggregating data via SQL scripting.
  • Extract, load and transform data (ETL) from structured and unstructured sources
  • Apply Natural Language Processing and Computer Vision to solve business use cases,
  • Strong skills in scientific data analyses, modeling, visualization and communication of results.
  • Knowledge of Python libraries (NumPy, Pandas, SciKit-Learn, TensorFlow, PyTorch), Spacy, MongoDB, PostgreSQL, Flask, streamlet and a good knowledge of data pipelines construction
  • Ph.D., M.S. or B.S. in Computer Science, Computational Physics, Operations Research, Geospatial Sciences, Remote Sensing Science, Environmental Sciences, Computational Astronomy or related scientific discipline


Must  have 

  • Understanding of various machine learning algorithms (e.g. SVM, Random Forests, Gradient Boosting, Log-Log regression, XGBoost, Lasso, Ridge, Clustering techniques, Neural Networks and others)
  • Regression (e.g. ? Linear/Logistic/MNL/Mixed Effects/Regularization)
  • Classification (K-means, Hierarchical, Latent Class, DBScan, SVM)
  • Dimension Reduction techniques (Principal Component analysis, Singular Value Decomposition etc.)
  • Optimization (Linear programming, Stochastic Gradient Descent, Genetic Algorithm etc.)
  • Experience with neural network approaches to text classification CNN, RNN, LSTM,Keras
  • Machine Learning algorithms? Neural Networks, Naïve Bayes, Bagging & Boosting, Random Forest
  • Distributed computing tools and cloud technology (AWS)

QUALIFICATIONS

  • Degree in Data Science, Computer Science, Engineering, Math, or Statistics preferred
  • At least 2 yrs of relevant experience in Data Science


SKILLS

  • SQL, statistical modeling, Feature engineering, Data visualization, Deploying models to production, Python programming, AWS, Domains(Healthcare/ Manufacturing/ Marketing/ Financial/ Telecommunication), powerbi/tableau, data warehouse

Benefits

  • Competitive Salary

  • Paid Relocation

  • Remote Support

  • Guaranteed Regular Salary Reviews

  • Job Type: W2 or Contract 1099 (full-time - 40 hours)

Employment Type: FULL_TIME