Data Analyst

Background:

• As a data specialist you will be supporting the entire Personalization area . While the topic is not new, the way we’ve organized it is. Previously we’ve focused the efforts in our department on Product Recommendations and Content Recommendations.
• With the addition of several teams from elsewhere in the organization, we’ve added new functionalities to our scope.
• The teams that were added provide us with customer-specific details by means of an API, have built several models to help us re-organize the layout of entire pages on Client based on historical behavior and customer details, and provide a sophisticated framework to do nudging and lotteries on client using very specific targeting and trigger details.
• In this new set-up we’re looking for someone that can help us bridge the gap between teams.
• Strategic: help leadership shape a strategy on how we would like to move forward with Personalization . What are the things the industry is doing; what are the things is doing today; and how can we grow further in this space with our values at heart.
• Organizational: the teams in the area should be able to derive new value from working together. Firstly, you will understand yourself what it is they do, identify overlaps and uniqueness, and help them get to know each other better and identify opportunities for further growth or to learn in collaboration.
• Operational: the potential of personalization is immense, even more so when you understand that the majority of our sales still happen in-store. It makes quantification of the potential that personalization has for particularly difficult. We are keen to get to know your ideas and thoughts on this and we hope you can help us make a better estimate of this going forward.

Requirements:

• Must: analytical skills, SQL, good stakeholder management, thinking on a more strategic level, certain extent of knowledge or experience when it comes to personalization (e.g. recommender systems, clustering / segmentation, modelling techniques for prediction).
• Nice: experience with GCP, Big Query, Python (Notebooks), familiar in an FMCG of retail sector, eager to learn, familiar in an eCommerce environment, experience building more strategic plans, experience with building business cases or assessing potential monetary gains on a complex topic.
• Analytical skills, thinking on a more strategic level, certain extent of knowledge when it comes to personalization.