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/      

As a Data Scientist, you will perform in-depth end-to-end analyses of incredibly large and complex datasets. Collaborating across multiple teams, your work will directly impact data-driven recommendations for growers and other external users. As one of the senior members of the team, you will work with autonomy and have opportunities to mentor more junior teammates.

 

Responsibilities:

  • Develop a comprehensive understanding of Indigo’s data structures, analytical tools, and metrics
  • Begin performing data fusion analyses including collection of data, data processing and normalization, and statistical modeling (and continue to do so on an ongoing basis with challenging deadlines)
  • Design and develop analytics to inform stakeholders in Research and Development about the results of Indigo Field Experiments and Commercial data at the sub- and cross- field level
  • Contribute to thoughtful integrative visualizations, analyses, and discussions of how field data both within and across fields informs our R+D pipeline and can be used to ground truth and explicate laboratory experiments

Competencies:

  • Extremely comfortable working with messy biological datasets from a variety of non-normalized sources and imbued with high level of ambiguity
  • Machine learning techniques for feature selection and exploratory analyses (e.g. clustering, LDA, etc.)
  • Enjoys capturing complex analysis problems; able to identify and apply appropriate advanced statistical analysis and machine learning techniques as necessary
  • Able to collaborate effectively with a very diverse set of teams and scientists (eg. agronomy, engineering, discovery, field sciences, logistics, operations research, product development and project management) and to understand their needs with a desire to teach quantitative skills to laboratory scientists and continually increase the level of sophistication in experimental design and analysis
  • Proactive and self-directed; enjoys autonomy while still mentoring and learning from teammates; a team player
  • Thrives in a fast-paced, growth environment
  • Excellent prioritization skills to deliver business and scientific value
  • Strong desire to continue learning, identify new techniques and technologies, and rapidly implement them to keep Indigo at the cutting edge (e.g. reading bioRxiv digests daily and testing new tools)

Qualifications:

  • PhD degree in a quantitative discipline (e.g. statistics, applied mathematics, engineering, physics, quantitative biology or similar) or equivalent practical experience
  • 2+ years industry experience in statistics and machine learning techniques applied to large, biological datasets.
  • Understanding of and experience working with biological and geospatial data, ideally from agricultural fields
  • 5+ programming experience including:
    •  A statistical and scripting language i.e. Python [preferred] or R
    •  Working experience with a wide range of statistical, geospatial, and machine-learning libraries in R or python is a plus
    •  Experience working with databases and SQL
  • Familiarity with linux/unix and high-performance computing environments such as AWS and Google Cloud Compute

 

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