Inovretail
Carlos Lopes has a diverse work experience in the field of technology and business. Carlos started their career at myPartner in 2011, where they held multiple roles such as Dynamics CRM Consultant, Software Engineer, and SharePoint Consultant. In these positions, they gained expertise in creating and configuring SharePoint solutions, developing webparts integrated with ERPs, and utilizing data view web parts and SharePoint Designer workflows.
In 2017, Carlos joined INOVRETAIL as a Technical Manager, responsible for overseeing technical operations. Carlos then moved on to become a Senior Delivery Engineer, where they demonstrated their proficiency in delivering projects successfully. Later, they took on the role of Delivery Manager, showcasing their leadership skills in managing project deliveries.
Currently, Carlos serves as the Head of Growth Professional Services BU at INOVRETAIL, where they are responsible for driving growth and managing professional services. Carlos'sextensive experience and skill set make him a valuable asset in the technology and business industry.
Carlos Lopes attended Universidade do Minho from 2008 to 2011, but the degree and field of study are unknown. Carlos obtained various certifications related to Microsoft Dynamics CRM and implementation. These include MS: Managing Microsoft Dynamics Implementations in April 2016, MS: Microsoft Dynamics CRM Customization and Configuration in January 2016, MS: Microsoft Dynamics CRM Application in July 2015, MCPS: Microsoft Certified Professional in January 2015, MS: Microsoft Dynamics CRM 2013 Applications in January 2015, MCTS: Microsoft Dynamics CRM 2011 Installation and Deployment in February 2014, MCTS: Microsoft Dynamics CRM 2011 Customization and Configuration in July 2013, and MCTS: Microsoft Dynamics CRM 2011 Applications in April 2013.
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Inovretail
InovRetail, a predictive analytics company focused on retail, working with players like Levi’s, Nike and others. 1. Predicting the sales baseline and the promotional impact for a Fashion retailer where they isolate what share of the sales are due to the Promotions in place, to the weather conditions, to a specific holiday and even to localfootball games – in some cases the difference between the predictions and the real observations are less than 2%!2. Predicting the churn patterns of another Fashion retailer’s clients, allowing them to predict who is more likely to churn and allowing them to take action before it is too late3. Predicting the products that are most likely to be out-of-stock and in what locations, optimizing the logistics and operations by several orders of magnitude – this is in place for Fashion, Food and now in Sports retailers.