National Agricultural Data Scientist

General Description of task(s) and objectives to be achieved

Under the overall managerial administrative leadership and supervision of the FAO Representative (FAOR) in Indonesia, over-all technical guidance from the technical officer in the Land and Water Division (NSL), with the technical backstopping of the Lead Technical Officer (LTO), in close collaboration with Ministry of Agriculture, the International Remote sensing and Data Scientist will: ·         Engage national partners and stakeholders to set up the national e-agriculture taskforce, undertake the needs and gaps analysis, develop the e-agriculture strategy and action plan; ·         Organise regular meetings with the project team, Ministry of Agriculture, Centre for Agricultural Data and System Information (CADIS), Strategic Agricultural Command Centre (KOSTRA TANI), partners of the Agricultural War Room development; ·         Provide technical support for reviewing and undertaking the needs and gaps analysis for the e-agriculture data system, including assessing the agricultural data management system, data accessibility, metadata, format, analysis methods for large data sets, quality control procedures, documentation, consistency, completeness, and comparability as well as the software used for data analytics; ·         Provide a report highlighting the linkage between national agricultural indicators and data; ·         Identify technical solutions related to agricultural data analysis in support to the e-agriculture strategy (e.g. template, metadata, classification, standards, QA/QC, management, integration etc.) and use for statistical data analysis (e.g. procedure, examples, modelling); ·         Pilot, test, validate and document technical solutions for two agricultural commodities, Coffee and Garlic in West Java, East Java and West Nusa Tenggara, using a combination of available data in MoA, field data and remote sensing applications; ·         Considering available data, data management and infrastructure system, engage national partners in designing an early warning system platform in MoA and in collaboration, considering identified key criteria and indicators, with a particular focus on data availability and sharing mechanisms; ·         Provide trainings to national staff on agricultural data, agriculture monitoring, data integrity and lessons learnt from various national programmes; ·         Contribute to national workshops related to digital agriculture systems (preparation of materials, presentation); ·         Provide technical guidance and examples of standard operating procedures related to to data (geospatial and tabular), land representation system, data management (collection, storage, security), data sharing (ownership, terms of use, agreements).

key performance indicators

Expected Outputs/ Deliverables: ·         Workplan prepared and regularly updated; ·         Minutes and proceedings of meetings and events organised; ·         Report presenting the results from the literature review and highlighting advantages and inconvenient taking into consider the national context and data availability; ·         Presentation and document explaining the methodological approach; ·         Report presenting the methodological approach and detailed steps, as far as possible using open source software, for replicability; ·         Guidance note provided to national consultants for data collection, field validation, meetings, and trainings; ·         Communication materials, factsheets, maps in support to national consultation with national partners prepared; ·         Technical recommendations for operationalization of the spatio-temporal dynamics of crop residue burning with statistical data at national level prepared; ·         Mission Reports (as required).

Requirement: ·         Advanced university degree in Geography, Engineering or Agronomy, Biological Science, or other Agricultural degree required; ·         +3 years of experience in spatial data handling and analysis, satellite data processing and management, GIS and remote sensing applications of for agricultural monitoring; ·         Hands on experience working on large data sets with expertise in data mining, predictive modeling, agricultural statistical analysis; ·         Prior experience to work with Government entities will be advantage; ·         Prior experience in providing training in agricultural monitoring; ·         Demonstrated expertise in SQL, database design, data modeling, data management and analytics; ·         Excellent skills in Python, Machine Learning, Cloud computing (e.g. GEE, Sepal), Supervised, Unsupervised Learning Models (Classification Models, Regression Model & Time Series), Cloud Analytics, Historical Agricultural analysis; ·         Excellent communication and workshop facilitation skills; ·         Working knowledge of English.

 

Duty station: Indonesia 

 

Duration: 6 months

 

General Note to All Applicants :

Interested candidates should submit a CV and a covering letter ( In English) clearly stating their relevant skills, experience and email to : FAO-ID@fao.org, Submission deadline : 20 April 2021. All candidates should possess computer/word processing skills. FAO reserves the right not to make an appointment at a lower grade or to make an appointment with a modified job description. FAO regrets to inform applicants that only short-listed candidates will be contacted.

Qualified female applicants and qualified nationals of non-and under-represented member countries are encouraged to apply. Persons with disabilities are equally encouraged to apply. All applications will be treated with the strictest confidence.