AXA Group Operations and Group Data, AI & InnovationIn recent years, significant work has been done to digitize AXA's business model. Nevertheless, due to massive technological changes, customers' expectations and behaviors have considerably evolved. Thus, we are convinced that we must accelerate our technological transformation to achieve our ambition to become an innovative tech-led company. Massive opportunities offered by data and new technologies arise both for our traditional insurance business and for new services to achieve our Payer to Partner ambition. AXA Group Operations sets the tone and must play its role as one of the major catalysts of AXA's global transformation.We are the ones triggering and empowering the evolution of our insurance business model through technology and innovation, driving its concrete implementation globally at speed, with a high quality of advisory and execution. Within AXA Group Operations, Group Data, AI & Innovation (GDAI) explores and scales the value of data, AI, digital transformation, emerging technologies (IoT, Geospatial, Blockchain, Quantum Computing, etc.) as well as innovative business ideas with the potential to disrupt the current insurance business model and to shape future opportunities to better partner in our customers' lives. GDAI and its spin-offs consist of 200+ inspiring minds located in Paris, Barcelona, London, Lausanne (on the EPFL campus), and San Francisco (on the Stanford campus) incubating and deploying solutions in co-creation and collaboration with AXA operating entities and strategic partners around the world.Purpose of the JobThe main mission of AI Research Executive Manager is to leverage in-depth knowledge of R&D topics to represent and act as a spokesperson for the research team towards stakeholders, including business. This role is crucial to support the execution of the TDO and BOOST with a particular focus on transversal streams. The AI Research Executive Manager is also responsible for bringing business knowledge and opportunities to the R&D activity. Additionally, the position includes representing, when necessary, the Group Chief Data Scientist in various instances.Main ResponsibilitiesManage TDO-R&D interaction: Representing and translating the teams' expertise to support the TDO execution in general, and in particular for the transversal streams.Manage BOOST-R&D interaction: Representing and facilitating the teams' work and expertise to support BOOST execution in general, and in particular for the CV satellite and Portfolio Analysis Use-Cases.Keep up to date and deeply understand the technical details of current R&D relevant for BOOST and TDO, including (but not limited to) LLMs, Satellite Imaging, Computer Vision, Responsible AI.Be the business-tech expert in LLMs and influencing business and tech communities accordingly.General understanding of the other R&D topics being covered by the R&D teams.Closely follow business challenges and objectives being treated inside TDO and BOOST. Identifying R&D actionable opportunities with direct business impact.Manage deep-tech expertise requests demands. Pilot budget and leverage TDO and BOOST fundings to meet target by managing external expertise and strengthening the team when necessary.Lead special missions/projects such as the ones identified via our strategic partnership program. This includes structuration (funding request, technical/business road-map, etc.) and execution.Represent group Chief Data Scientist when necessary (e.g. in regulatory think tanks, internal and external events and/or communities).As a senior member of the team, providing guidance to teammates to navigate topics at the frontier of business and advanced tech (i.e. not research) as for instance, satellite imaging, sustainable AI, LLM market watch, AI governance, AI culture and training.Your ProfileA PhD in Technology, Computer Science, Data Science, or a related field.Excellent knowledge of Data Science / Machine Learning technical aspect with a focus on large language models and computer vision.Experience as a Data Scientist on several projects or as Project Manager in Data science projects.Experience in using technology and data/AI to drive business growth and operational efficiency.Deep understanding of core insurance business processes, products, associated data and technical risks.Thorough knowledge of Innovation project lifecycle.Strong business acumen, with experience in a role that required aligning data, AI and/or technology initiatives with corporate strategic objectives, preferably in the insurance or financial services industry.Excellent communication and influencing skills, with extensive experience engaging with C-level executives and external stakeholders.Ability to work in an international and cross-functional organization.Proven track record in leading multi-disciplinary teams.
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