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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, with a strong foundation in machine learning and deep learning methodologies. Capable of integrating cross-functional insights to drive discovery in microbial and natural products solutions.
Highest-signal resume keywords
Machine Learning MethodsDeep LearningPython ProgrammingPredictive ModelingData Integration
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Predictive ModelingMachine LearningDeep LearningData AnalysisModel CalibrationStatistical AnalysisGenomic Data IntegrationMetabolomic Data IntegrationBiochemical Hypothesis GenerationResearch Problem Framing
Soft Skills
Verbal CommunicationWritten CommunicationTeam CollaborationCritical Evaluation
Tools & Technologies
PyTorchGenerative AI MethodsCloud Computing PlatformsMLOps PracticesContainerizationWorkflow Orchestration
Industry Keywords
Data ScienceBiologyChemistryNatural ProductsMicrobiologyAI/ML MethodsIntegrative ModelingDigital Twin ModelingAgentic AI SystemsCross-Functional Teams
Tech Stack
Tools & technologiesCloudPythonPyTorch
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 to identify opportunities that might otherwise be missed within a single pipeline
- Evaluate and implement modern AI/ML methods, including deep learning and modern architectures, to advance predictive modeling capabilities
- 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 math 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
- Ability to work as part of a cross-functional project team
- Preferred: experience with multi-modal, integrative, or digital twin modeling approaches
- Preferred: experience integrating genomic, metabolomic, and/or phenotypic data for predictive modeling
- Preferred: experience with generative AI approaches applied to life sciences
- Preferred: experience or education in natural products chemistry/biochemistry or microbiology
- Preferred: experience deploying ML models to production, with MLOps practices such as version control, containerization, workflow orchestration, and reproducible, maintainable pipelines
- Preferred: practical knowledge and experience with cloud-computing systems and platforms
- Preferred: experience with agentic AI systems or tool-use/multi-agent architectures
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
- Paid holidays
- Excellent parental leave which includes a minimum of 16 weeks for mother and father
- Competitive retirement savings plan
- Tuition reimbursement program