Junior Data Agronomist in Sugarbeet Area

hace 3 semanas


En remoto, España HEMAV Technology A tiempo completo

THIS POSITION IS OPEN IN UNIBO (UNIVERSITÀ DI BOLOGNA) IN THE FRAMEWORK OF WATER AI BASED SUPPORT TOOL - WAIST.

THE POSITION IS IN SPAIN BUT THE CANDIDATE WILL BE HIRED BY UNIBO, NOT HEMAV.

At HEMAV we are an AgriTech StartUp founded in 2012 working passionately on Data Science in the agrifood industry with the purpose of generating more food with less environmental impact.

️ We use a unique approach, for yield forecasting based on Artificial Intelligence using satellite technology and other data sources (drone, meteo, soil, etc.).
Users of our technology leverage their decision-making systems on
information and knowledge generated on a field-by-field basis, with
customized per-user models.

The HEMAV family is currently composed by a team of around 50 persons with offices in Spain, Brazil, Peru and the USA. We have around 50 regional partners distributed between more than 17 countries in Europe, America and Africa. More than 7.000 users have access to the platform with service in 5 million Hectares.

**❤️ HEMAV values are**:

- Teamwork: We are a familiy and 'fly and process' together
- Passion: We wake up every morning to change the world
- Simplicity: Less is more. Technology should simplifies our lives, not complicates it
- Excellence: We pursue our best version and learn from our values
- Integrity: What you see is what we are
- Innovation: We have a creative attitude against challenges

LAYERS, our software, generates key yield forecasting data. In addition, it offers analytics to the agricultural sector with a large direct impact. For example, clients can improve the efficiency in treatments (sowing, fertilization, irrigation, etc.) and generate
estimations in yield (tonnes per hectare), as well as quality estimates (e.g. soybeans protein quantity) for different crops. We know that producers, the agroindustry itself, or even insurance companies and traders in the agronomical sector are facing three main challenges, with a large impact in their gross margin:

- Crop Management
- Production yield and logistics
- Economical yield
- Climate change risk assessment

LAYERS helps minimize these risks through a high-quality continuous monitoring and predictions. We want to make LAYERS the core of all the yield-related decisions in the agribusiness value-chain using data and statistics. Our slogan is

“Reshaping the future increasing land efficiency”

The LAYERS Product Team is the main area of the company, where 15 persons are distributed in three squads: Data Engineering, Data Intelligence, BackEnd and UX/UI. Three-four weeks sprints are combined with sprint demos where all the company is updated with the news in the product by all the members of the product team.

Some of the things you should consider when joining our team are:

- Young and friendly environment
- Flexible work-hours
- 100% remote work
- Flexible remuneration system that adapts the salary to your needs
- Extra holidays

LAYERS, is composed of a web-app, mobile-app and API. Our software constitutes the heart of the customer ecosystem where data analysis and prognosis are presented in analytical and insightful web dashboard formats. Thanks to this, our customers can monitor their crops and perform better business decisions in their agro-industrial companies.

Tasks

️ Position

THIS POSITION IS OPEN IN UNIBO (UNIVERSITÀ DI BOLOGNA) IN THE FRAMEWORK OF WATER AI BASED SUPPORT TOOL - WAIST.

THE POSITION IS IN SPAIN BUT THE CANDIDATE WILL BE HIRED BY UNIBO, NOT HEMAV.

What is your mission in WAIST?

Main goal of this position is to have a key role in the data collection campaigns that will be carried out in the sugarbeet areas in Spain while scientific data analysis will be carried out within the UNIBO tasks in the project. Important part of the work is expected to happen in the field.

Collaboration in the identification of new agronomical insights and tools for WAIST future users relaying on the new data and tools. Helping users to move towards sustainable and more efficient agriculture.

Collaboration in the development software, models, repositories, and continuously work in improving the Data infrastructure, models and project development. Exchanging information and knowledge with data scientists, agronomists, analysts and other experts in the project. Attendance to workshops and other events is foreseen.

Global improvements in the use and impact of WAIST will as well be part of the tasks this person will face.

✍ Tasks

**Specifically, this person will**:

- Plan, execute and review data sampling campaigns with LAYERS.
- Give support in the design, planification and implementation of the WAIST developments ensuring agronomical perspective.
- Implement crop-specific solutions designed in collaboration with the HEMAV, Azucarera and AIMCRA teams.
- Design, give feedback and eventually maintain the toolset and

functional processes in the framework of the agronomical data handling
and modelling, following the coding stand



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