Associate Scientist Data Analyst- ICRISAT
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Job Summary
- Assist ICRISATs scientists in planning agricultural field trials.
- Generate randomizations and trial layouts for field experiments.
- Provide support to the scientists for data curation simple and complex analysis and interpretation of the results from varying disciplines.
- Develop R codes and/or refine existing R codes for data curation visualization and analysis.
- Actively contribute to scientific publications in peer-reviewed journals.
- Contribute to conducting training programmes for both ICRISATs scientists and National Agricultural Research Scientists (NARS) in data management and data analysis.
- Perform any other task assigned by the supervisor.
Requirements
- A Ph.D. in Statistics or a closely related field with at least 3 years of relevant experience in agricultural research which is highly desirable.
- Proven experience working as a Biostatistician in a research environment or applied setting.
- Strong analytical and problem-solving skills with demonstrated expertise in applied statistical analysis.
- Solid knowledge and practical experience in experimental design.
- Experience in data generation management and curation.
- Proven capability in predictive modelling and advanced statistical techniques.
- Proficiency in statistical and data analysis software including R Python and SAS.
- Sound interpersonal and problem-solving skills
- Demonstrated ability to work independently as well as in a team setting.
- Preferably having experience of working in multi-cultural and interdisciplinary teams.
- Experience in an international organization environment will be an added advantage
- Ability to prioritize and organize work efficiently and independently.
Required Skills:
A Ph.D. in Statistics or a closely related field with at least 3 years of relevant experience in agricultural research which is highly desirable. Proven experience working as a Biostatistician in a research environment or applied setting. Strong analytical and problem-solving skills with demonstrated expertise in applied statistical analysis. Solid knowledge and practical experience in experimental design. Experience in data generation management and curation. Proven capability in predictive modelling and advanced statistical techniques. Proficiency in statistical and data analysis software including R Python and SAS. Sound interpersonal and problem-solving skills Demonstrated ability to work independently as well as in a team setting. Preferably having experience of working in multi-cultural and interdisciplinary teams. Experience in an international organization environment will be an added advantage Ability to prioritize and organize work efficiently and independently.
