Data Science Engineer Lead

What you'll do at Fall Creek:

• Design, engineer, and maintain complex, multi-modal databases for plant phenotypic and environmental data from multiple sources.


• Develop, test, and implement data quality models within data processing pipelines.


• Implement data governance standards, including metadata and data provenance tracking.


• Support company-wide initiatives for AI data readiness.


• Act as a liaison between R&D and IT teams, such as translating data collection needs from biologists into guidance for data pipelines.


• Acting as a technical domain expert collaborating with regional colleagues on data science projects, such as designing horticultural management experiments, statistical analysis of breeding trials, and processing of climate time-series data for integrating into forecasting, genomic selection, or other models.


• Communicate project results to technical and non-technical stakeholders across regions, supporting the improvement of variety development.


• Collaboratively and critically evaluate and incorporate new data collection technologies aimed at improving breeding methodologies.


• Adhere to company values and treat colleagues with respect.

What you bring to Fall Creek:

REQUIRED QUALIFICATIONS
 

• One of the following: a Ph.D. degree in a relevant field, a Master’s degree in a relevant field with 3 years of experience,
  OR a Bachelor’s degree with 5 years of relevant experience.


• Strong background in data modeling, ETL processes, and database design.


• Hands-on experience with data pipeline tools, experience building and maintaining in-house data products, proficiency in SQL, Python, and/or R, and familiarity with version control (Git).


• A commitment to ethical action and adherence to humanistic values of humility, skepticism, and curiosity.


• Demonstrated ability to work effectively as part of a cross-disciplinary and diverse, international team.


• Demonstrated ability to independently identify opportunities and to support and prioritize requests from stakeholders for data processing, engineering, analysis, and visualization needs.


• Excellent organizational skills, able to manage multiple projects from diverse stakeholders.


• Excellent oral and written communication skills, with emphasis on ability to translate technical data science concepts for diverse, non-technical audiences.


• Bilingual proficiency in English and Spanish.

PREFERRED QUALIFICATIONS

• Familiarity with biology or related fields such as agricultural science, horticulture, plant breeding, ecology, or environmental science.


• Experience with interactive data visualization programs such as PowerBI or Shiny.


• Experience evaluating high-throughput plant phenotyping or precision agriculture technologies.


• Familiarity with AI data readiness principles.


• Familiarity with Microsoft SharePoint platform