Yield Prediction

vor 6 Monaten


Home Office, Schweiz Dnext intelligence Vollzeit

**Responsibilities**

You will analyse weather and satellite data as well as historical yield data for several different crops and use this data to produce a set of features to be train different machine learning models and compare their efficiency at predicting end-of -season crop yields. The resulting machine learning model will provide in-season predictions and analysis of the feature importance of different inputs to the yield prediction model.

The work will be done in collaboration with crop analysts and data scientists who will provide help accessing and analysing data as well as guidance regarding the analysis of crop production data.

**Qualifications**
- Proficient in Python, familiar with Python tools and data formats used to analyse data and build machine learning models (pandas, scikitlearn, pytorch, Stan, etc.)
- Knowledge of applied statistics and basic experience analysing weather and environmental data, experience analysing time series data
- Bonus: basic knowledge of agriculture, meteorology, remote sensing
- Ability to teamwork, genuine interest in learning more about agriculture and commodity markets

Type d'emploi : 100%, Stage
Durée du contrat : 3-6 mois

Programmation:

- Du Lundi au Vendredi
- Période de travail de 8 Heures

Types de primes et de gratifications:

- Primes

Lieu du poste : Télétravail