Arnaud Benoits

Chez Siloe, nous aidons les agriculteurs et les professionnels de l'agriculture à identifier et mobiliser facilement les financements publics accessibles pour leurs différents projets de développement. Pour en savoir plus : https://www.siloe.io/

• Worked on predicting the payment date of invoices with Python and R using Survival Analysis and Machine Learning techniques. • Built automated dashboards on Tableau to follow performance KPI's and analyse clients' profile. Daily use of PostgreSQL. At Fluidly we’re defining the new category of Intelligent Cashflow, to help business owners sleep better at night and provide visibility of their financial future. Historically, cashflow management has been stressful, time-consuming, theoretical and expensive. Fluidly provides the only AI-powered cashflow forecast that requires no modelling whatsoever, using transaction-level detail to produce an accurate financial prediction in minutes. Since our launch in 2016, we’ve been working to provide confidence, certainty and control around cashflow to thousands of SMEs, in partnership with leading accounting firms. Fluidly has been named a ‘Hot 10’ European Fintech by the Fintech50, listed in WIRED’s Top 100 Hottest European startups and won various Accounting Excellence awards. We’re backed by leading financial technology investors (Octopus, Nyca and Anthemis) and have a diverse team drawn from leading firms and universities. In June 2019, Fluidly was awarded £5M as part of the RBS Alternative Remedies Package, to drive commercialisation of financial technology for SMEs.

• Organised a 2-month mission to install solar panels in an off-grid community of Gawad Kalinga in the Philippines. • Raised 4k€ on fundraising platforms to finance the mission.

• Implemented the SEM (Seach Engine Marketing) Strategy of several clients using various channels and tools such as AdWords, Facebook Ads, Bing Ads, Google Display Network, Google Analytics. • Optimised the follow-up of the accounts with scripts on AdWords Query Language (AWQL). • Built automated dashboards on Google Data Studio.

• Managed product development of a platform for a client in the mining sector, developing an eco-driving contest algorithm on Python. Daily use of classic Python libraries (sklearn, pandas, numpy, scipy) • Estimated market growth potential in Africa and ensured implementation of the platform in a new country • Developed a predictive algorithm on R to help lots’ pricing for a client in the real estate sector