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Masters degree in Agriculture / Environmental Science / Mathematics / Biostatistics, Doctor degree optional Sound understanding of the concepts of statistical modelling e.g. linear and logistic regression modelling, Bayesian modelling, linear mixed modelling Knowledge of model validation techniques and application Proven experience in data analysis and model development Self-motivated towards learning and upskilling Good programming skills in Python and/or R Familiarity with version control systems e.g. GitHub Excellent communication and presentation skills to effectively convey complex topics / results to stakeholders with non-technical backgrounds Good sense of team work and flexibility with work timings (ability to work with global teams) Good cross-cultural skills, deep respect for different cultures, gender and diversity. Fluency in English, knowledge of additional language such as German is preferable.