Location: San Francisco / Fremont / Sacramento, California or remote due to COVID-19
The role of Agricultural Data Science intern is to develop Machine Learning & Artificial Intelligence Mathematical Models to predict Macro Level agricultural outputs such as: productivity of crop, seasonal influence, gree agriculture, crop price prediction, demand prediction, safety & healthy aspects of cattle and sucess factors for small farmers.
As a Data Science major, you will be a leading researcher and a practitioner of application of data science to solve the societal issues, especiall agricultural & dairy farming. Additionally, you would have a passion for animal husbandry and respect & sincere gratitude and respect to take care of farmers world wode. As a Farmer, you will be industry lead bridge between farmer needs and Information Communication Technology (ICT) team.
Skills:
Python (Scikit-learn, PyTorch)
Jupyter Notebook
Supervised, Unsupervised Learning Models (Classification Models, Regression Model & Time Series)
Public Cloud Computing
Machine Learning Cloud Analytics - Amazon Sage Maker, Microsoft Azure Machine Learning Studio, Google
Agricultural Economics (Familiarity with USDA Datasets, World Organization, US Data.Gov and other countries agricultural strategies)
Historical Agricultural analysis - Wheat, Rice, Dairy, Soy, Corn and other major fields
Exposure to Veterinary science
Familiarity with agricultural imports/exports
Per capita consumption
Climate influence on agricultural output
Hydro and Water resources & dynamics due to population change & climate change
Skills and Experiences
• Excellent people & leadership skills.
• (Optional) Exposure to Software, Hardware, Mobile Devices and Sensors.
• Good communication skills
• Care and Love for Humanity and beyond.
• (Optional) Paper based Data Collection & Sketching.
• A passion for innovation and outside box thinking
Please Submit your Resume to hiring manager skedari@hanuinnotech.com or hr@hanuinnotech.com
Location: San Francisco, CA
Posted: Aug. 28, 2024, 12:17 a.m.
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