Soil Health Data Scientist
Indigo is reinventing the way the world cultivates its food and fiber. By harnessing beneficial microbes and digital technologies, Indigo enables growers to produce higher quality harvests that both enhance the surrounding ecosystem and improve human health. Indigo then connects these growers to buyers who seek differentiated products. To build a more beneficial agriculture, Indigo enables farmers to reliably earn more profit, to sustainably feed billions of people, and to dramatically improve the planet we live on. 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. www.indigoag.com
Systems Innovation is the idea factory for Indigo. We are an interdisciplinary team of business, science, and technology professionals that drive radical change in agriculture through new systems of farming.
To develop and deploy these systems, we:
- Identify, create, evaluate, and accelerate new opportunities that span technological and business innovations. We drive these innovations.
- Draw inspiration from our own diverse experiences but are always seeking perspectives from a broader ecosystem of internal and external stakeholders.
- Establish a strategic vision but are not afraid to get in the weeds on operationalizing a new business unit.
- Set ambitious goals and stretch our limits but take the time to pause and reflect on our work.
The role of Soil Health Innovation Scientist will develop algorithms that quantify soil carbon sequestration and analyze the effects of regenerative agriculture. Indigo is creating a world-leading carbon credit market for agriculture and pastureland, and crucial to that carbon credit market is developing a scalable way to measure changes in soil carbon. This role will develop machine learning algorithms that predict carbon concentration, bulk density, and other soil metrics using mid-infrared (MIR) spectroscopy, as well as algorithms that transfer calibration across spectrometers. This scientist will then analyze this data and other measurements taken on thousands of farms in the Terraton Experiment, which will soon become the world’s largest study on regenerative practices and soil health. By making statistical inferences and beautiful visualizations, this scientist will answer key hypotheses for scientific publications that quantify the benefits of regenerative practices.
- Develop understanding of statistical underpinnings of soil carbon measurement
- Become familiar with Indigo’s data platform and associated Looker reports and tables relevant to Indigo Carbon and the Terraton Experiment
- Build relationships with key stakeholders in relevant teams (Carbon, Agronomy, Field Data Solutions, GeoInnovation, Indigo Research Partners, Business Intelligence, etc.)
- Own project on machine learning with mid-infrared (MIR) spectra:
- Assess the state of the art of predicting carbon concentration and bulk density from MIR spectra
- Develop a prototype for predicting carbon concentration and bulk density from MIR spectra that can be deployed for an academic paper for the Terraton Experiment
- Work closely with the Data Science Engineering team to deploy a robust MIR carbon measurement product
- Develop models for predicting other soil characteristics using MIR spectra
- Develop a way to seamlessly integrate new data into the MIR spectral library
- Own project on analyzing and visualizing data for Terraton Experiment:
- Refine and develop data pipelines for collecting, processing, and analyzing experimental data about carbon, bulk density, nutrients, water aggregate stability, and more.
- Establish relationships with data scientists focused on analyzing the microbial sequencing data.
- Work with BI analysts to build tools to track the flow of data and to check its quality.
- Produce compelling visualizations and statistical inferences that form the heart of an academic journal article on how regenerative practices affect soil carbon.
- Highly collaborative - able to work across functions
- Comfortable with large datasets
- Creative problem solver; when faced with incomplete data or an obstacle to interpretation, able to find ways to generate insights
- Strong communication skills; able to communicate complex statistical concepts in simple language and with beautiful visualizations of data
- Can prioritize effectively among competing priorities
- Comfortable with ambiguity and creating clarity in ambiguous situations
- Ability to meet deadlines, sometimes challenging ones
- Able to complete all tasks, even menial ones, with a positive attitude
- Passionate about Indigo’s mission
- 3+ years’ work experience in a data science capacity required
- MS/PhD with research involving data science—such as statistics, physics, applied mathematics, bioinformatics, economics—is required
- Experience prototyping and implementing machine learning models required
- Experience with analytical method development or scientific instrumentation preferred (for work on MIR spectra)
- Familiar with one or more of the following areas of statistics: experimental design, analysis of experimental data, sampling (e.g., stratified sampling), geospatial statistics, power analysis
- Proficient in programming in Python, SQL, Git required
- Familiarity with business intelligence platforms like Looker preferred
- Experience working with spectral libraries preferred (for work on MIR spectra)
- 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.