MatHem’s Tech-organization consists of agile cross-functional teams of talented people dedicated to creating an experience world-class for our customers with our website, app, and supply chain. We’re highly ambitious when it comes to taking MatHem to the next level through tech, and always strive to be at the forefront of technology and encourage innovation highly. With employees and leadership with backgrounds from top tech-companies, we’re taking the grocery space from offline to online, helping people save time for people to do more of what they love.
Our work environment is creative and humble with a lot of heart, where everyone’s thoughts and ideas matter. And hey, if you feel like a break, there’s probably always someone that’s up for some ping pong or playing video games!
Our Product teams are always striving to create an even more excellent customer experience than yesterday and deliver products that solve problems. The rapidly growing product team is responsible for the end-to-end user journey, thus innovating across our e-commerce and supply chain, to provide the best grocery shopping experience and to drive sustainable growth. Our product team includes product managers across eCommerce and supply chain, a product design team, and a product insights team, driving data-driven innovations in an agile and cross-functional way.
In our Development teams, we solve complex challenges, build great solutions, and develop new features to make the shopping experience both better and faster. Our code should always be testable with a focus on high-quality, and we like to work together to bring new code and ideas to MatHem. We’re working with pure cloud serverless architecture and modern microservices, and strive to continuously nurture a curious and forward-leaning approach to software development, evaluating new technologies as well as open source.
Our Data team provides MatHem’s organization with all the data and insights needed to build the best solutions for our customers. We work with designing and building data models to improve accessibility, efficiency, and quality of data - as well as applying statistics and machine learning to solve problems at scale ranging from improving our end-user experiences to optimizing warehouse and distribution quality and efficiency.
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