Squadra Machine Learning Company
Fenna van Daele currently serves as an Account Manager at Squadra Machine Learning Company, a position held since 2020, focusing on market developments, strategic marketing plans, and client acquisition. Prior to this role, Fenna worked as an ICT Advisor at Moore DRV from May 2015 to November 2017, providing companies with guidance on optimal software and hardware solutions while enhancing ICT processes. Fenna holds a Master's degree in Marketing Management from Tilburg University (2018-2020) and a Bachelor's degree in Computer Science from the University of Amsterdam (2014-2018), complemented by secondary education at Barlaeus Gymnasium (2008-2014).
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Squadra Machine Learning Company
Squadra Machine Learning Company is an innovative Dutch company which combines knowledge about business processes, algorithm development and data visualization for the purpose of helping customers with Machine Learning algorithms and the application of Artificial Intelligence solutions. We have a passion for Data Science and Machine Learning in particular. With a dedicated team of Data Consultants, Data Engineers and Data Scientists, we help our customers to automate various business and industrial processes, customer-oriented services and other data-driven functions in an innovative way. We offer services in the following areas: • Projects: Turn key Data science projects to reduce operational costs, increase revenues or realize new service and business models with the customer’s data • Products: A collection of standard AI solutions in the value chain of Supplier – Wholesale – Retail, especially around Smart Product Management, Supply Chain Optimization and AI-commerce. Squadra Machine Learning Company works for Bol.com, Intergamma, Blokker, Vereniging Eigen Huis, Sligro, BCC, Sonepar, Intratuin, Rensa, Office Depot, PPG, Ingram Micro, ETIM International, 2BA, Kaemingk and many others. Squadra Machine Learning Company is a proud part member of Squadra – the Data Driven Value Creation Network.
Employees
11-50