Maya Azouri

Maya Azouri is a Product Manager within TheFork's Recommendation & Ranking Tribe, since February 2024. In this role, she focuses on building the vision and strategy for ranking systems, using artificial intelligence to improve the user experience and drive company growth. Maya is responsible for redesigning the ranking system, ensuring it keeps pace with the latest technological advances and meets user needs. She also leads data-related initiatives, including acculturation programs, to promote a data-driven culture within the organization, and ensures teams are well equipped to use data effectively, supporting informed decision-making and innovation.

From March 2022 to February 2023, Maya was Product Owner for data solutions at TheFork, on the demand (B2C) side. She worked closely with domain leads to co-build the domain's vision and roadmap. Her role included gathering and translating business needs into solutions, prioritizing requirements, and delivering solutions in line with best practices for quality and data management, using an agile methodology. She also coordinated teams, maximized delivery across the various teams working on these solutions, and ensured a high level of SLA and solution scalability.

At Novencia Group, from May 2021 to February 2022, Maya worked as a Data Product Owner. She managed analytics and data science projects across several sectors, including automotive, finance and utilities. She led data governance strategies, oversaw the rollout of data management platforms and supported project management for various use cases. She was responsible for the entire rollout of the data governance strategy, overseeing data science projects and supporting teams in implementing innovative solutions.

From January 2019 to May 2021, Maya worked at Quantmetry, part of Capgemini Invent, as a Senior Data Consultant. She led analytics and data governance projects in the automotive industry and the financial sector. She managed project portfolios, defined data strategies and supported the rollout of data platforms. She also worked on profile recommendation projects for internal mobility and information extraction from documents, as well as large-scale data governance projects, overseeing the entire rollout of the group's data governance strategy.

From September 2017 to June 2019, Maya took part in various HR and talent management projects, including performance management, training, career management and talent acquisition. She set up key performance indicators for recruitment and training, co-built training plans with HR managers, and regularly tracked employees to ensure good talent management and retention. She also led the recruitment process, developed relationships with target universities, and oversaw employer branding and HR analytics projects.