Senior Biostatistician
Há 3 dias
The position of Statistician is available within our Digital and Data Science team. We seek an expert in statistical analyses and reporting to support the delivery of agronomic field trials, co-manage experimental design and results interpretation for Crop Protection Development, drive digital transformation initiatives in R&D through innovative data methodologies, develop data science tools and services, train field trial teams on statistical best practices, integrate diverse internal and external data sources for comprehensive analysis, and stay current with agricultural statistics to implement cutting-edge methodologies.
Key Responsibilities:
- Guarantee good statistical practice is applied in Crop Protection Development activities, with special attention to design of experiments.
- Closely work with product-line teams in statistical and data-analytics work applied to development projects, beginning to end.
- Help in the transition to digital methods applied to agriculture (e.g., digital data capture, predictive modelling).
- Develop and implement a strategy to foster best practice in data analytics and participate in projects within the area of responsibility.
- Provide documentation, training material and deliver training courses to maintain and improve trial design and analysis standards for global/regional/country users (field scientists, technical managers, others as necessary).
- Provide the appropriate statistical input to various CP R&D projects (e.g., plot-size optimization, crop density & crop-protection program optimization, trial-placement optimization).
Required Skills and Qualifications
Required:
- Profound knowledge of statistics methods and their application in agronomy and/or biology.
- Proficiency in English is must.
- Advanced technical knowledge of the R statistical programming language. Other statistical suites (e.g., SAS, STATA, JMP) and programming languages (e.g., Python, Java, C++) are an asset.
- Good theoretical understanding of the principles of experimental designs applied to agronomic trials.
- Agile mindset, with focus on delivery of results in constant contact with stakeholders. Training in Agile Project Management methods and/or experience in start-up companies is an asset.
- Good knowledge of Git or other version-control systems for software development and reproducible-science work.
- Postgraduate degree in statistics or in natural sciences with a heavy component of statistics.
- Strong background in statistics- and data science-oriented programming languages (i.e., R, Python)
- Strong knowledge and understanding of statistical methods such as meta-analysis, mixed effect modeling, longitudinal modeling, Bayesian methods, design of experiments, etc.
- Strong knowledge of scientific modelling methods and their applications to applied questions.
Desired:
- PhD is preferred.
Benefits
We offer a culture that celebrates diversity & inclusion, promotes professional development, and strives for a work-life balance that supports the team members. Our benefits package includes flexible work options, full medical, dental & vision, paid vacation, paid holidays, maternity and paternity leave, education assistance, wellness programs, corporate discounts, and more.
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