Appsilon is an ambitious and fast-growing software house and consultancy specializing in decision support systems and machine learning with Fortune 500 clients across the globe. We are a unique company driven by a mission to improve our society and environment. Some examples of our #AI4good work include contributing to animal preservation in Gabon Parks, building COVID-19 dashboards, and improving data science tools for Doctors Without Borders.
We are a global leader in R and Shiny, which are used by companies of all sizes to build analytical applications. When companies run into difficult problems or want to initiate large-scale enterprise projects, they come to Appsilon.
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Every few months we start completely new projects and dive into a completely new world. One day we learn the secrets of promotions in retail chains, another day we analyze satellite images, and then we get super interesting data from the residential market for analysis. Our projects are not only an opportunity to test our skills in difficult statistical, algorithmic, and technological problems but also an opportunity to learn how many different industries work from the inside.
At Appsilon, you can expect a flat organizational structure. There are currently 30 of us in a tech team, and each person has their own specialization, so the selection of projects and people who work on client tasks is flexible and depends on who has time to take on additional tasks at any given moment. We have other R/Shiny specialists, Frontend Developers, Fullstacks and DevOps in our team – you will have the opportunity to meet and work with each of them.
We are looking for a specialist whose experience and knowledge will enrich our team and allow us to take new, previously unknown directions.
Basic tasks will include:
You are good for this role if you:
What’s in it for you:
What can you expect during the recruitment process?
Every few months we start completely new projects and dive into a new industry. One day we might discover the secrets of promotions in retail chains, another day we might analyze satellite images using machine learning. Our projects are not only an opportunity to test our skills in difficult statistical, algorithmic, and technological problems but also an opportunity to learn how many different industries work from the inside.
In this app, you can explore an AI model that the Appsilon AI team built for the xView2 competition. The model locates buildings and assesses damage sustained after natural disasters.
This app allows for an interactive exploration of disaster risk and development indicators in Madagascar.
When we build scalable and reliable enterprise dashboards, we focus on UX and a modern aesthetic that improves our models' functionality.