Director of In Silico Breeding

POSTED: August 31, 2021
BUSINESS: Inari Agriculture, Inc.
START DATE: Immediate Availability


As Director of In Silico Breeding, you will be responsible for leading a cross functional team to design step change products by boosting our predictive capabilities. The right candidate enjoys a “start-up” atmosphere and is flexible, shows good judgment, takes initiative and is willing to take on a variety of tasks and responsibilities as needed to achieve goals and deliverables. Excellent communication skills are essential for this role as part of an interdisciplinary team. This role is based out of West Lafayette, Indiana, and reports to the Sr. Director of Pre-commercial and Product Development.  The responsibilities of this role includes the following:

  1. Drive and build in the predictive platform to accelerate the identification of relevant haplotypes and acceptance by internal and external partners
  2. Contribute to a genomic selection program to identify favorable individuals for advancement into subsequent generations
  3. Contribute to the overall product creation aligned with defined  product concepts, including the optimization of breeding programs 
  4. Prototype, Develop and Scale genetic and agronomic models to enhance germplasm use as well as commercial solutions
  5. Design and validate new schemes aiming to accelerate  time to market across the breeding pipeline
  6. Develop and implement germplasm and breeding strategies incorporating new technologies to guide germplasm selection, including accelerated line and hybrid development by rapid recycling of parents and genomic selection
  7. Bring the power of computational capabilities and genetic algorithms to various aspects across the company. Closely collaborates with the product design team to integrate genetic diversity analyses into the discovery of causal sequences
  8. Incorporate up-to-date scientific knowledge, data, and modeling approaches to develop and test new crop and genetic models and their deployment into pipeline risk predictions


  • Provide technical contributions in a fast-paced Products team environment to accelerate our efforts on building a data-driven pipeline. 
  • Leverage the latest advances in quantitative genetics, predictive analytics and optimization algorithms to identify and drive the development and deployment of new methodologies globally, 
  • Be responsible for predicting and optimizing our product pipeline and improving the probability of success of our products. 
  • Develop sustainable, consumable, accurate, and impactful reporting on model inputs, model and observed outputs, business impact, and key performance indicators.
    • Collaborate with the engineering team and the Predictive Modelling Director to co-develop digital solutions to support product development activities and increase the efficiency of the process. These include, but are not limited to: processing, storage and visualization of molecular data, haplotypes and pedigrees; generation of genomic predictions and environmental characterization; supporting organization and tracking of breeding programs and supporting databases.
    • Build, manage, and lead a team of Data Scientists. 
  • Closely collaborates cross functionally across the company, partnering  with the Science and Commercial teams frequently to ensure step change product development by applying innovative science and approaches 
  • Design and prototype models that integrate artificial intelligence techniques, optimization, and statistics in order to solve challenging analytics problems influencing product developments using scalable models
  • Solve computational challenges of scaling complex AI algorithms on big data with engineer partners
  • Drive the adoption of data and predictions to guide decisions, and foster a data-driven culture throughout the company by providing tools that enable self-service analysis.


  • Solid foundation in quantitative genetics, plant genetics/breeding, crop science or soil science with particular emphasis on commercial agriculture and current agronomic best practices
  • PhD in Breeding, Crop Science, Agronomy or similar discipline with 5 years of industry experience (preferred); or MS in Breeding, Crop Science, Agronomy or similar discipline with 10 years of experience (required)
  • Experience with modeling crop development, growth, biotic and abiotic stresses, and yield for different economically important crops
  • Programming skills in at least one data science language (Python or R preferred)
  • A strong sense of purpose and drive to develop unique, high impact solutions
  • Adaptability and enthusiasm for new challenges, innate curiosity, and a passion for learning
  • Creative and strategic thinking, willingness to be bold and take risks, and the ability to recognize and learn from failure
  • A collaborative mindset that is open to giving and receiving ideas, perspectives, and feedback
  • Ability to work both independently and deliver on responsibilities within a highly collaborative environment
  • Ability to effectively communicate with a diverse range of individuals and audiences


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