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Data Internship is a Washington-state based agtech startup, focused on empowering growers with data. Our focus is on data insight capabilities, drawing from on-farm/off-farm, online/offline data sources to enable growers to make informed management decisions. 

Almost all growers are struggling with data silos, and seek simplification and data unification aligned toward actionable ROI-driven insights. Our solution is initially focused on permanent crops - starting with apple orchards, Washington's largest crop, and enable growers to differentiate in the global economy by improving crop yield and managing costs and challenges related to labor, water, weather, and chemicals. We're building a platform to expand across the US and internationally.


This role is focused on bringing together disparate data sources from partners, organizing data into 'layers' on mapping systems, enabling growers to plan & execute decisions on labor, nutrients, & irrigation. Position is remote / home-based; preference for candidates in PST.


The ideal candidate's favorite words are learning, data, scale, and agility. You will leverage your strong collaboration skills and ability to extract valuable insights from highly complex data sets to ask the right questions and find the right answers. 



  • Analyze raw data: assessing quality, cleansing, structuring for downstream processing

  • Data pipeline: advanced knowledge of Python to pull data from data/IoT partners via APIs; knowledge of Azure Data Factory a plus.

  • Database management: maintain SQL & MySQL database services

  • Data interpretation, visualization, & mapping: Manage and layers of soil, water, nutrient, yield, labor data onto API-based mapping services

  • Collaborate with engineering team to bring analytical prototypes to production

  • Generate actionable insights for business improvements



  • Enrollment in quantitative field (Statistics, Mathematics, Computer Science, Engineering, Management Information Systems, etc.)

  • Precision agriculture context and training strongly preferred.

  • At least 1  years' of experience in quantitative analytics or data modeling

  • Understanding of predictive modeling, machine-learning, clustering and classification techniques, and algorithms.  

  • Fluency in a programming language (Python, R, C, C++, Java, SQL)

  • Documentation with Git tools (GitHub)

  • Preference given to students in Washington State work-study program

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