Scientific Lead, Data Science

Equinom is a seed breeding company that uses DNA sequencing and proprietary algorithms to make the breeding process more efficient. The company has used this technology to produce varieties of legumes, sesame, and special grains targeted to the global food industry.

The company seeks a data scientist to lead the development of the next generation of advanced analytics to accelerate the development of seed products optimized for field performance and value-added quality traits.

Main responsibilities

  • Develop prototype level research for predictive seed product discovery consuming diverse high-throughput data sets from the field, genomics, and biochemistry laboratories.
  • Bring data science perspective to value-added seed product development through experimental design and algorithms development.
  • Play a leading role in guiding colleagues in breeding, agronomy, genomics, and biochemistry in applying Bayesian and machine learning tools for accelerating the development of value-added seed products.
  • Plan experiments to generate new datasets for application in predictive breeding for enhancing the nutritional quality in multiple crops.
  • Contribute to the development and implementation of automated procedures for analyzing data and delivering products for increased efficiency and accuracy of breeding programs.


  • Ph.D. in Quantitative Genetics, Computational Biology, Plant Breeding, or relevant fields.
  • Proven ability to handle disparate data sets in both structured and unstructured formats related to genomics, breeding and food biochemistry.
  • Proven experience developing and applying advanced analytic methods in an industry breeding setting.
  • Direct experience in analyzing complex and diverse datasets that aid product development.
  • Proficient in applying advanced deep/machine learning AI analytics (CNN, NLP, Clustering, RF, SVM, etc.) and deep learning frameworks.
  • Proficient in programming languages (Python, R, etc.) and experience in applying visualization tools (Tableau, QlikView, Spark, Kafka, etc.).