Data Scientist, Machine Learning at Indigo
What if nature could be harnessed to help farmers sustainably feed the planet? Since 2014, Indigo has questioned agriculture's full value chain to improve grower profitability, environmental sustainability, and consumer health. The company’s scientific discoveries and digital innovations have amplified new value from soil to sale, benefiting more than 10,000 growers to date. Indigo is also the company behind The Terraton Initiative, a global effort to drawdown one trillion tons of atmospheric carbon dioxide by unlocking the potential of agricultural soils. In 2019, Indigo was ranked #1 on CNBC’s Disruptor 50 list. Headquartered in Boston, MA, Indigo has additional offices in Memphis, TN; Research Triangle Park, NC; Sydney, Australia; Buenos Aires, Argentina; Basel, Switzerland; and São Paulo, Brazil.
The role of the Data Scientist, Machine Learning will build scalable solutions to generate insights from a broad set of Indigo data assets, ranging from high-resolution machine data to various remote imagery sources. The new hire will join a cross-functional team building an analytics engine that leverages data flowing from innovative field experimentation within the Indigo ecosystem, yielding data products that serve multiple internal and external customers. In addition, this role will use this unique grower ecosystem to prototype algorithms and tools for Indigo Fields, our distinctive software product that empowers grower decision-making to sustainably and profitably produce food while generating carbon credits.
- Build tools leveraging Indigo’s extensive data assets to yield better insights from experiments, bringing value to internal and external customers.
- Contribute to recommendation engine codebase that drives grower action by using valuable intelligence from Indigo Research Partners, the unique research ecosystem Indigo runs on commercial growing operations.
- Design, build, and run generative models and simulation frameworks in order to gain understanding of statistical power to detect effects in our recommendation engine.
- Develop scalable algorithms for Indigo Fields software product focusing on the processing and cleaning of high-resolution machine data.
- Develop a comprehensive understanding of Indigo's existing systems and data assets.
- Take ownership of the statistical rigor behind our automated modeling; able to consistently identify areas of improvement and move towards implementing critical upgrades.
- Prototype rigorous, quantitative models that can improve the insights and performance of our spatial analytics delivered to our customers.
- Present results to both technical and non-technical audiences to effectively communicate technical merit and business value of their work.
- Actively contribute to team code review and collaborative coding community, as well as internal seminars on topics of expertise (machine learning, statistics, quantitative modeling).
- Extensive quantitative and modeling background; comfortable making simplifying assumptions in the construction of complex models, as well as building generative models and simulation frameworks to understand statistical power of real-world applications.
- Strong coding skills, able to inherit and improve an existing codebase; writes well-documented, clean, maintainable code in a collaborative environment.
- Demonstrated ability to implement ML in a scalable fashion; able to think through design decisions to minimize effort take to move modeling frameworks into production.
- Thrives in a fast-paced environment, able to succeed through cross-functional collaboration.
- Proactive, self-directed, and able to think critically while being solution-oriented.
- Highly organized and demonstrated thought leader; able to influence without authority.
- Comfortable working with messy data-sets from a variety of non-normalized sources; can instill order and standardization.
- Strong communication skills; able to translate results of complex analyses into interpretable results, both visually and verbally.
- Enjoys capturing complex analyses problems; able to identify and apply appropriate advanced statistical analysis techniques as necessary.
- Excels at communicating data analysis at the interface of business and data science via documentation and concise language.
- 2+ years in professional data science setting building ML prototypes and/or implementing ML in production-level code.
- Masters or Ph.D. with a quantitative focus (i.e. computer science, physics, computational biology).
- Fluency in python and SQL required, fluency in R preferred.
- 1+ years’ experience working with Agile or Scrum processes preferred.
- Experience with spatial data analysis, data aggregation, and geovisualization.
- Practical experience with at least one deep learning platform.
- Strong experience with cloud computing (AWS preferred).
- Familiarity with agriculture-specific data sources and use cases preferred.
- This role is based in Boston, MA.
Indigo is committed to living our values, specifically “creating a work environment where everyone feels respected, connected, and has opportunities to learn and grow.” As part of living our values, we strive to create a diverse and inclusive work environment where everyone feels they can be themselves and has an equal opportunity of succeeding.