Indigo improves grower profitability, environmental sustainability, and consumer health through the use of natural microbiology and digital technologies. Utilizing beneficial plant microbes and agronomic insights, Indigo works with growers to sustainably produce high quality harvests. The company then connects growers and buyers directly to bring these harvests to market. Working across the supply chain, Indigo is forwarding its mission of harnessing nature to help farmers sustainably feed the planet. The company is headquartered in Boston, MA, with additional offices in Memphis, TN, Research Triangle Park, NC, Sydney, Australia, Buenos Aires, Argentina, and São Paulo, Brazil. http://www.indigoag.com/      

The Geospatial Data Content Manager trains the ISA team on data collection from scouting apps and precision ag equipment and serves as the intermediary between field and data sciences team for cleaning ingestion. 

 

Responsibilities:

  • Lead creation of data collection targets and tools to ensure consistent collection of data and data standardization. 100% of data collected aligns with data science team requirements.
  • Develop in-field training plans for (Certified) and Indigo Solutions Advisors and growers that demonstrate and promote an understanding of how data can be used and ingested at a growing scale.
  • Plant Monitor Setup & Harvest Monitor Setup
  • Yield monitor calibration and loading planting varieties
  • Create and implement central point of data aggregation and preprocessing of data collected by Indigo Solutions Advisors (ISA) and Tech Service Representatives including on-farm data and remote monitoring equipment.  This would include: yield, farm treatments, irrigation, soils, satellite and drone imagery. Aggregate data from 100% of Commercial Indigo acres and 75% of historical acres on commercial fields.
  • Transfer consistent data set to support data science team in development state-of-the-art machine learning tools to understand crop yields as a function of microbiome, crop, planting conditions, soil, weather, farm treatments, and farm conditions. Work with data science team to produce compelling and clear visualizations of agronomic and statistical findings.
  • Manage and lead precision ag programs (Sirrus) to facilitate data capture in the field.  
  • Work with data science team to analyze agricultural data to understand the impact of agronomic decisions (Pre-plant, in-season and Post-Harvest) on crop health, crop yield and ultimately farmer profitability.  Work with data science and tech service team to develop digital tool utilized by field agronomy team.  This tool will be used to drive data driven actionable advice to 100% of Indigo customers.

Competencies:

  • Outstanding communication skills - Outgoing and enthusiastically enjoys explaining data collection process and norms. 
  • Demonstrated ability to present and train in real-world situations while demonstrating hands-on application of data collection software and hardware.
  • Demonstrated ability to communicate data collection process with data science team and other functional groups across the organization.
  • Demonstrated ability to develop data standardization processes. 
  • A curious, scientific mind dedicated to tearing apart new results through careful, quantitative analysis joined with sound scientific practice.
  • Extremely strong customer focus, seeing growers and ISA’s as our key end users, and grower success as our ultimate goal.
  • Easily adapts to new types of problems and questions.  Flexible to different types of analysis and different stakeholders (e.g. lab science, fields trials, commercial team).
  • Adapts well in a fast pace environment.
  • Deep understanding of modern Bayesian statistics, ensemble classifiers, regression algorithms, as well as off the shelf machine learning techniques.

Qualifications:

  • Bachelor's Degree required, Master's Degree preferred + 2-5 years industry experience in a relevant field such as agronomy and geospatial data collection and analysis
  • Experience in and/or eagerness to learn about agriculture, agronomy, GIS, spatial statistics, plant biology, microbiology, agricultural economics and financial hedging, and the plant microbiome.
  • Familiar with production agriculture inputs and management decisions
  • Experience with model validation and evaluation, and data imputation
  • Familiar with all major monitors and commercial software programs
  • Experience working in industry and a dedication to Data Science performed in an industry setting
  • Must be able to travel up to 50%
  • Must be familiar with regional specific crops (i.e. rice, cotton, wheat, corn, soybeans)

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