Geospatial Data Science Intern: Vineyard Analytics & AI

E. & J. Gallo Winery

Modesto (CA)

On-site

USD 25,000 - 44,000

Full time

8 days ago
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Benefits offered by this job

Medical and dental coverage
401k plans
Profit sharing
Pet insurance
Employee wine shop access
Company holidays

Job summary

E. & J. Gallo Winery invites applications for a GIS (Geospatial Data Science) internship focused on advancing wine grape production.

You will analyze geospatial data from satellite imagery, soil maps, climate data, and ground observations to support yield, fruit composition, and wine quality improvements. You'll work with experts across Winegrowing Research, using Python, R, and cloud computing to automate spatial data tasks and contribute to high-quality spatial databases for vineyard

Qualifications

  • Currently enrolled at a college or university pursuing a Bachelor's or Master's in Computer Science, Engineering, Agricultural Sciences, Life Science, or Natural Resources.
  • Available for the entire duration of the internship program.
  • Strong applied technical skills and analytical problem-solving.
  • Good oral and written communication skills.
  • Requires availability to work evenings, weekends and holidays when necessary.
  • Must be 21 years of age.

Responsibilities

  • Develop GIS and remote sensing solutions for advancing vineyard management and grape production practices.
  • Apply machine learning to monitor crop health, disease detection, yield prediction, and vine water status.
  • Process and analyze geospatial data from satellite and drone imagery, soil maps, climate information, and ground observations.

Job description

E. & J. Gallo Winery invites applications for a GIS (Geospatial Data Science) internship focused on advancing wine grape production.

You will analyze geospatial data from satellite imagery, soil maps, climate data, and ground observations to support yield, fruit composition, and wine quality improvements. You'll work with experts across Winegrowing Research, using Python, R, and cloud computing to automate spatial data tasks and contribute to high-quality spatial databases for vineyard

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