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Corteva Agriscience — ауыл шаруашылығына бағытталған, тұқым, өсімдіктерді қорғау және цифрлық ауыл шаруашылығы шешімдерін әзірлейтін ғылыми-технологиялық компания. Оның қызметі фермерлерге өнімділікті арттыруға көмектесуге, ауыл шаруашылығын тұрақты жүргізу тәжірибелерін қолдауға және ұзақ мерзімді азық-түлік қауіпсіздігіне үлес қосуға бағытталған. Компания заманауи ауыл шаруашылығындағы күрделі мәселелерді шешу үшін агрономия, технология және инновация салаларындағы сараптаманы біріктіреді.
Biologicals Discovery Data Scientist
Use machine learning and deep learning to connect Corteva’s microbial and natural products discovery data. Help develop crop health solutions by identifying and advancing promising candidates.
Сипаттама
- Apply data science across chemistry and biology to discover microbial and natural products for crop health.
- Build predictive models from genomic, metabolomic, and phenotypic data to assess and prioritize candidates.
- Combine findings across discovery pipelines to uncover opportunities that individual pipelines may miss.
- Assess and apply current AI and machine learning approaches, including deep learning, to strengthen predictive modeling.
- Work with colleagues in data science, engineering, genomics, metabolomics, chemistry, and biology.
- Advance integrated discovery pipelines, guiding candidate prioritization, selection, and development of microbial and natural products solutions.
Талаптар
- A master’s degree and at least five years of post-graduation work experience, or a PhD, in a quantitative field such as data science, statistics, mathematics, or computer science, or in a life or physical science such as biology or chemistry.
- Strong biological knowledge and the ability to assess model outputs critically and develop testable, business-relevant biological and biochemical hypotheses.
- Demonstrated experience with modern machine learning and deep learning methods.
- Practical experience with a current AI toolkit, such as PyTorch, transformer architectures, or generative AI methods.
- Sound understanding of mathematics and model behavior, including training design, evaluation metrics, and calibration.
- Ability to frame research questions independently, set success criteria and evaluation methods, and communicate findings clearly.
- Strong Python or comparable programming skills for data preparation, analysis, and machine learning applications.
- Excellent written and verbal communication skills.
- Ability to contribute to a cross-functional project team.
- Preferred: experience with multimodal, integrative, or digital twin modeling.
- Preferred: experience combining genomic, metabolomic, or phenotypic data for predictive modeling.
- Preferred: experience applying generative AI in life sciences.
- Preferred: education or experience in natural products chemistry, biochemistry, or microbiology.
- Preferred: experience deploying machine learning models to production and using MLOps practices, including version control, containerization, workflow orchestration, and reproducible, maintainable pipelines.
- Preferred: practical knowledge of cloud computing systems and platforms.
- Preferred: experience with agentic AI systems or tool-use and multi-agent architectures.
Артықшылықтар
- Development opportunities to build your skills.
- Health coverage for you and your family starting on your first day of employment.
- Four weeks of paid time off and two weeks of well-being pay each year.
- Paid holidays.
- Parental leave of at least 16 weeks for mothers and fathers.
- Retirement savings plan.
- Tuition reimbursement program.
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