OVRSEA

The team is organized in squads. Before the beginning of each quarter, "burning problems" are defined from the OKR. These "burning problems" correspond to strategic objectives, such as improving the onboarding of customers, or the billing time. The product managers then work in collaboration with a team to create the features that will allow them to reach the objective on the quarter.

Squads are formed at the beginning of each quarter, based on the affinity between the developers and the subject under consideration. For example, for a frontend topic, a squad with a UX designer will be formed. The squads then work independently throughout the quarter.

Five values structure our culture, which are :

• Pedagogy : many of the tech members have learned to code at Ovrsea. We foster a teaching culture so that all members can keep learning no matter how experienced they are.
• Caring : we strive to create a humane environment where people feel at ease while being able to continuously grow,
• Excellence : we give much importance to writing clean code and development best practices,
• Questioning : we’re always looking for ways to improve our code, infrastructure and product vision,
• Reliability : we are all committed to doing things right

Each transport is different (mode of freight, local regulations, cargo...) and requires a thorough knowledge of the business. However, the tasks to be carried out are very similar for the same type of transport !

We therefore opted for a "product over process" approach and designed a low-code system, Opflow, which allows specialists to encode the different tasks to be carried out for each type of transport themselves. Freed from the need to know the rules perfectly, operational staff can devote themselves to high value-added tasks.

The next steps are to cover as many types of transport as possible and to automate certain tasks.

Transporting goods for a customer is the basis of the freight forwarding business. But we can go even further by allowing customers to track the quantity of each product reference transported. This is the aim of the "Stock Vision" project which combines Product Research, Machine Learning and Development. The data source is often in paper format, which makes this feature difficult and ambitious to implement. But it has already started to charm many customers and there are still many challenges ahead !

• HR call with our Talent Acquisition Manager (30 min)
• Live case study with our team (1h00)
• Fit and project interview with Nicolas, our Engineering Manager and Antoine, our CTO (1h30)
• Speed recruiting with the team in our offices (2h00)