Indigo | Associate Data Scientist, Crop Modeling | United States | United States | BigDataKB.com | 2023-01-27

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Job Location: United States

Job Detail:

About Indigo

Indigo Ag is a mission-driven company dedicated to harnessing nature to help farmers sustainably feed the planet. We innovate across a breadth of technology and science disciplines to help enhance agriculture’s long-term sustainability and profitability and mitigate the climate crisis. We seek to positively impact the world through the digital and biological solutions we bring to the market, creating a more resilient earth, healthier economies, and thriving communities. Our people build partnerships, explore the science, and engineer the technology to help grow the future of sustainable agriculture. The only way to achieve it is through a unique combination of expertise – from Fortune 500 to academia, soil science and agriculture, to tech start-ups.

Indigo’s Biological Products organization develops products based upon our deep understanding of the plant microbiome. The company has commercialized such products for cotton, wheat, barley, corn, soybeans, and rice in North America, Latin America, and Europe under the biotrinsic™ brand. Our R&D and product development teams are working to continue to develop products that address the growing number of abiotic and biotic stresses that crops experience worldwide. The company is headquartered in Boston, MA, with additional offices in Memphis, TN, Research Triangle Park, NC, Basel, Switzerland, Buenos Aires, Argentina, and São Paulo, Brazil.

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The R&D data science team is responsible for the analysis of our Global R&D Field Trials, with the overall goal of leveraging data to accelerate the discovery and launch of best-in-class commercial products. The Crop Modeling Associate Data Scientist will play a key role in developing and applying crop models and data analytics approaches for performance insights and product advancement decisions. You will work in close partnership with the R&D field scientists, Product Management, and Commercial teams to deliver innovative modeling solutions in alignment with key business priorities

The ideal candidate will be team oriented, excited by new challenges, comfortable in a fast faced and dynamic environment, and have a strong interest in deriving performance insights from agronomic data. We are a cross-functional team that values collaboration, teamwork, open communication, and growth and learning.

Responsibilities:

  • Analyze model outputs and support the delivery and communication of crop model outcomes
  • Calibrate crop models to make sure simulated yield and stress level reflect reality. If necessary, design and conduct specific experiments for model calibration
  • Support product performance understanding based on modeling outputs
  • Write robust, well-documented code that adheres to community standards and data science best practices
  • Build algorithms for crop models with a focus on analysis/prediction of the impact of abiotic/biotic stresses, cultivar/genotype, and crop management on overall crop productivity
  • Stay current on crop modeling research, and explore new approaches by applying the latest advancements in crop physiology and modeling
  • Explore diverse environmental, remote sensing, and/or geospatial datasets
  • Support the education of stakeholders to promote the application of crop modeling results for decision making
  • Analyze the quality of input data, and work with the data management team to resolve issues

Competencies:

  • Proficient in building clear and organized code (R or Python)
  • Passion for clear, thorough, and timely documentation
  • Excellent communicator and strong team player
  • Able to prioritize conflicting demands and comfortable with ambiguity
  • Strong desire to continue learning by identifying and implementing new techniques and technologies
  • Focused on the needs of customers and experience working directly with stakeholders to implement usable data products
  • Able to work productively in a multi-disciplinary and predominately remote team with geographically dispersed stakeholders
  • Passion for achieving Indigo’s mission

Qualifications:

  • MS in Plant Physiology, Agronomy, Crop Sciences, Statistics, Soil Science, Environmental Sciences, or other highly quantitative discipline with a focus on biological problems
  • Fluency in R and/or Python programming and basic SQL programming
  • Experience in popular relational databases, such as MySQL, MS SQL, Snowflake
  • Experience parameterization and validation of crop models to understand environmental impacts and genetic effects on yield performance
  • Experience with crop models such as DSSAT and APSIM
  • Experience working with biological and agronomic data
  • Experience with Linux command line, AWS environment, and parallel computing
  • Experience with data management and data visualization is a plus

At Indigo, we are committed to providing an environment of mutual respect where equal employment opportunities are available to all applicants and team members. All employment decisions are based on business needs, job requirements, and individual qualifications, without regard to race, color, religion or belief, sex, pregnancy (including childbirth, lactation, and related medical conditions), national, social or ethnic origin, age, physical, mental or sensory disability, marital status, family or parental status, sexual orientation, gender identity and/or expression, family medical history or genetic information, military and veteran status, and any other characteristic protected by applicable law. Indigo believes that diversity, equity, and inclusion among our team members are critical to our success. We seek to recruit, develop and retain the most talented people from a diverse candidate pool.

If you’re applying for a job in the U.S. and need reasonable accommodation for any part of the employment process, please email [email protected] and let us know the nature of your request and contact information. Please note that only those inquiries concerning a request for reasonable accommodation will be responded to from this email address.

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