Location: Boston, Massachusetts, United States
Engage/collaborate with a team of Scientists from multiple biological disciplines:
To help integrate environmental, phenotypic, and molecular datasets, and build solutions to support our genome edited-product development pipeline across different crops in our pipeline.
- Develop computational models.
- Implement machine learning and/or other non-linear or linear algorithms
- Work with Products, Science, and Digital teams to develop, prototype, and implement data pipeline and front-end applications
- Contribute to our ongoing germplasm characterization efforts
- Contribute to the development of highly accurate training sets.
- Develop, improve, or expand in-house computational pipelines, algorithms, models, and services used in crop product development.
- Constantly document and communicate results of research on data mining, analysis, and modeling approaches.
- Ph.D. in Computational Biology, Data Science, Computer Science, Bioinformatics, Plant Biology, Quantitative Genetics, Genetics and Genomics, or other relevant scientific fields.
- Expertise with tools for data analysis, statistical computation, and visualization (such as Python, R); programming and pipeline development skills integrating large, complex datasets from distinctive structured and unstructured sources.
- Demonstrated skills to use simple interfaces to build visualization capabilities of analysis outputs and results.
- Demonstrated experience developing and executing machine learning, deep learning, and data mining algorithms, statistical methodologies, and/or other predictive and simulation models.
- Experience with complex, multi-source, multi-year, and multi-location biological datasets typical of agricultural systems.
- Experience working with various types of molecular and genetic data, including DNA, RNA, metabolites, proteins.
- Familiarity with molecular marker-based studies applied to plant breeding, such as marker-assisted selection, genome-wide phenotype-to-genotype association, and genomic selection.
- Outstanding problem-solving skills and proven ability to develop, deliver, and deploy analytical solutions by: scoping the problem and defining hypotheses, identifying and using necessary data sources, building pipelines for data integration, analysis, modeling, and simulation, validating models, and prototyping actionable outcomes.
- Ability to align and integrate data science research into crop product development pipelines and materials.
- Ability to efficiently summarize and effectively communicate results to a wide variety of audiences; strong communication skills.
- Ability to work in a fast-paced, cross-functional, collaborative environment, completing projects on time.
- Creative, innovative, and strategic thinking; willingness to be bold and take risks on novel ideas.
- Curiosity and a desire to continuously learn and have a meaningful impact.
- A collaborative approach, open to giving and receiving ideas, perspectives, and feedback.
- Experience in agriculture, plant or animal breeding.
- Experience w: AWS, Docker, Git, Jupyter, APIs.
- Experience in genomic selection to plant/animal breeding.
- Experience with genome editing.
Complete the form below to apply for the Data Scientist / Machine Learning role: