In less than a decade, ManoMano has become a key player in the home improvement and renovation sector. Launched in 2013, ManoMano is the reference online marketplace for DIY, home improvement, and gardening. Co-founded by Philippe de Chanville and Christian Raisson, ManoMano brings together the largest offer of DIY and gardening online products, including electricity, plumbing, hardware, frames, indoor and outdoor furniture, and tools. With more than 2,600 seller partners and 7.5 million products, ManoMano currently employs 600 people and operates in six markets: France, Belgium, Spain, Italy, Germany, and the United Kingdom.
Motivated by the prospect of improving the living environment of their customers and convinced of the importance of the home market for sustainable consumption habits, the ManoMano teams aim to help write a new chapter in an industry that is struggling to reform itself. ManoMano brings to this highly technical world the power of its sector expertise, combined with data and digital capabilities, to offer customers easy access to innovative advice, products, and services 100% online.
The ambition of the Founders and the team at ManoMano is to accompany this sector transformation with a strong culture of boldness, within an ingenious and frugal organization that places people and teams at the heart of the company's development.
Mission
The position is located within the Analytics team in the Data department. Your role will involve collaborating with other Data Analysts to cover the analytical needs of the Commerce & Operations Department. You will play a key role in two of ManoMano's main objectives:
To achieve these objectives, the data analysis team provides strong insights, creating and improving powerful reports for stakeholders to monitor performance, progress, and make informed decisions.
Key Responsibilities
Performance Monitoring:
Data Modelization and Analysis:
As part of the ManoMano data team, you will be highly involved in improving our data usage in collaboration with other teams (data science, data engineering, etc.).
Who You Are:
Requirements:
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