Team Lead â€“ Raleigh/Durham, NC
- Asthe Environmental Modeling Team Lead, you will drive innovation in decisionsupport tools for product development in agriculture combining appliedmathematics, biology, and predictive analytics. As a technical team lead, youwill lead a multi-disciplinary team of computational scientists in transformingdata (e.g., environmental, crop performance, genetics) into knowledge to enabledecision support across the Seeds pipeline.
- Youwill also help drive the transformation of environmental, crop performance, andgenetics data into knowledge for the design, development, and placement of cropsolutions. As an environmental modeler, you will develop and apply modeling andpredictive analytics approaches to enable the prescriptive design anddevelopment of seed products. You will work in close partnerships with expertsin research, development, breeding and commercial teams, regional and globalcrop teams, and external partners to deliver innovative modeling solutions inalignment with key business priorities.
- Leadthe RTP Modeling team, providing innovative mathematical modeling and predictiveanalytics competencies to the organization in support of trait discovery, theend-to-end breeding pipeline, crop protection R&D, and commercial needs.
- Supportthe R&D and Commercial pipelines by providing technical leadership,direction and management of a team of multi-disciplinary computationalscientists to deliver and apply mathematical modeling and predictive analytics capabilities to enable data-driven decision support.
- Guidethe development and deployment at scale of complex biological systems andenvironmental modeling combined with predictive analytics approaches to enhance decision support for keybusiness processes.
- Drivethe innovation within Syngenta in the area of mathematical modeling and predictiveanalytics research, promoting scientific excellence of the RTP Modeling team,maintaining a network within the scientific community in these fields, andbringing new concepts into Syngenta R&D in a timely fashion to support ourindustrial innovation leadership.
- Buildeffective partnerships with leaders to enable delivery of model-driven anddata-driven innovations in alignment with business needs.
- Provideresearch subject matter expertise and prototyping in the development ofdecision support tools embedding biological modeling, environmental modeling,or predictive analytics in partnership with the internal R&D organizationon information technologies.
- Maximizescientific, operational, and procedural excellence and efficacy.
- Asa member of the Modeling Leadership team, you will contribute to thedevelopment and implementation of a predictive modeling strategy for mathematicalmodeling and predictive analytics in support of R&D.
- Asa technical expert you will develop and/or apply novel and existingenvironmental and mathematical modeling approaches to data (e.g.,environmental, crop management and performance, and genetics) for environmentalcharacterization support to the R&D and Commercial organizations.
- Promotethe use and application of mathematical modeling and predictive analyticscapabilities for biological and environmental problems through solidcross-functional partnerships.
- Providescientific leadership and technical knowledge to scout and evaluate newopportunities in predictive analytics and modeling.
- Ph.D. or equivalent experience in Applied Mathematics, Biomathematics, Bioengineering, Environmental Sciences or a related field.
- Understanding of applied mathematics, modeling, computational science, predictive analytics and plant biology required for the accountabilities above.
- Understanding of the Seeds and Crop Protection business to develop appropriate modeling or predictive analytics research programs and strategy.
- 5 years of experience applying environmental or mathematical modeling in a scientific/R&D environment, preferably in agriculture or other life sciences.
- Experience working effectively in multi-disciplinary teams.
- Experience working with the end-to-end modeling process for complex systems, including problem formulation and model development, calibration, validation, application and deployment.
- Ability to drive the development and implementation of innovative and novel modeling and predictive analytics methodologies and applications for Syngenta, in alignment with the predictive modeling strategy for Modeling.
- Ability to create, champion, lead, prioritize, and coordinate innovative research project activities across diverse scientific, professional and cultural backgrounds.
- Ability to clearly communicate research plans, drivers, and progress to business stakeholders, project leaders, research managers and technical partners.
- Ability to integrate into a highly diverse team comprising multiple disciplines, nationalities, and cultural backgrounds.
- Ability to build trusted partnerships and drive the application of mathematical modeling and predictive analytics for decision support across Syngenta R&D.
- Workproductively in a team / matrix environment with geographically dispersedstakeholders.
- Experience applying predictive analytics in a scientific/R&D environment is highly preferred.
- Full Benefit Package(Medical, Dental & Vision) that starts the same day you do
- 401k plan with companymatch, Profit Sharing & Retirement Savings Contribution
- Paid Vacation, 12 Paid Holidays,Maternity and Paternity Leave, Education Assistance, Wellness Programs, CorporateDiscounts among others
- A culture that promoteswork/life balance, celebrates diversity and offers numerous family orientedevents throughout the year
is a leading agriculture company dedicated to feeding the world and improving
global food security by enabling millions of farmers to make better use of
available resources. We are committed to rescuing land from degradation,
enhancing biodiversity and revitalizing rural communities. We have 28,000
people in over 90 countries working to transform how crops are grown.
is an Equal Opportunity Employer and does not discriminate in recruitment,
hiring, training, promotion or any other employment practices for reasons of
race, color, religion, gender, national origin, age, sexual orientation,
marital or veteran status, disability, or any other legally protected status.
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