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Biologicals Discovery Data Scientist
Corteva Agriscience. Innovate at the interface of data science, chemistry, and biology to drive discovery of novel microbial and natural products solutions for crop health .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in developing predictive models using genomic, metabolomic, and phenotypic data, while applying modern AI/ML methods such as deep learning. Strong ability to evaluate model outputs and articulate findings within cross-functional teams.
Highest-signal resume keywords
Predictive ModelingMachine LearningDeep LearningPython ProgrammingData Analysis
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
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Hard Skills
Predictive ModelingMachine LearningDeep LearningData WranglingModel CalibrationStatistical AnalysisBiochemical Hypothesis EvaluationMathematicsGenomic Data AnalysisMetabolomic Data Analysis
Soft Skills
Verbal CommunicationWritten CommunicationCross-Functional CollaborationProblem FramingArticulation of Findings
Tools & Technologies
PyTorchTransformer ArchitecturesGenerative AI MethodsAI Stack
Industry Keywords
Data ScienceBiologyChemistryQuantitative FieldsNatural ProductsMicrobial SolutionsDiscovery Pipelines
Tech Stack
Tools & technologiesPythonPyTorch
About the role
Key responsibilities & impact- Innovate at the interface of data science, chemistry, and biology to drive discovery of novel microbial and natural products solutions for crop health
- Develop predictive models integrating genomic, metabolomic, and phenotypic data to characterize and prioritize promising candidates
- Build models connecting insights across discovery pipelines
- Evaluate and implement modern AI/ML methods, including deep learning and modern architectures
- Partner with data scientists, data engineers, genomics and metabolomics scientists, chemists, and biologists
- Drive integrated discovery pipelines and candidate prioritization, selection, and advancement toward new microbial and natural products solutions
Requirements
What you’ll need- Minimum MS with 5+ years of post-graduation work experience, or Ph.D., in quantitative fields (e.g., Data Science, Statistics, Mathematics, Computer Science) or in life or physical sciences (e.g., Biology, Chemistry)
- Strong understanding of biology, with the ability to critically evaluate model outputs to generate testable and business-relevant biological and biochemical hypotheses
- Demonstrated experience with modern machine learning and deep learning methods
- Hands-on experience with a modern AI stack (e.g., PyTorch, transformer architectures, generative AI methods)
- Solid understanding of mathematics and model behavior, including appropriate training design, evaluation metrics, and model calibration
- Ability to independently frame a research problem, define success criteria and evaluation approach, and clearly articulate findings
- Strong foundation in Python or a similar programming language for data wrangling, analysis, and ML applications
- Excellent verbal and written communication skills with ability to work as part of a cross-functional project team
Benefits
Comp & perks- Numerous development opportunities offered to build your skills
- Health benefits for you and your family on your first day of employment
- Four weeks of paid time off and two weeks of well-being pay per year, plus paid holidays
- Excellent parental leave which includes a minimum of 16 weeks for mother and father
- Competitive retirement savings plan
- Tuition reimbursement program