Hatim Bendahhane

• Subject: Led the technico-functional design and delivery of internal Generative AI solutions across several BPCE entities, including CIB, enabling employees to securely query proprietary document repositories through RAG-based assistants. Acted as the bridge between business requirements, AI capabilities, and banking security and compliance constraints. *Project scoping & functional design: Led the qualification and scoping of GenAI use cases, defining project objectives, functional requirements, success criteria, stakeholders, and technical or regulatory constraints prior to implementation. *RAG solution design: Translated business needs into functional and technical requirements, contributing to key design choices around document ingestion, chunking, embeddings, retrieval, reranking, prompt orchestration, and source traceability. *Cross-functional delivery: Coordinated AI, Data, IT, Cybersecurity, Compliance, and business teams throughout the project lifecycle, managing dependencies, risks, validation phases, and readiness for production. *AI evaluation & optimization: Defined evaluation frameworks for retrieval relevance, answer quality, hallucination reduction, source grounding, latency, and user satisfaction, and worked with technical teams to identify optimization levers. *Business adoption & continuous improvement: Led workshops and user testing sessions, challenged business requirements against technical feasibility and GenAI capabilities, and translated feedback into solution improvements and prioritized evolutions. Tech & tools: LLM, RAG, Retrieval, Prompt Engineering, AI Evaluation, Python, SQL, Agile methodologies, stakeholder management.

• Subject: Led the end-to-end management of an AI-powered recruiting platform project for the EIT, bridging technical, product, and business needs. Responsible for defining the roadmap, aligning stakeholders, and ensuring successful delivery of innovative AI solutions tailored to the recruiting and talent-matching domain. * Product & strategy definition: Identified high-value AI use cases in recruiting, structured the business needs, and translated them into a product roadmap with both quick wins and transformative milestones. * Project scoping & execution: Drove the full lifecycle of AI projects, from ideation and feasibility assessment to implementation and adoption, including risk analysis. * Cross-functional coordination: Acted as the interface between stakeholders (EIT leadership, IT teams, data scientists), ensuring alignment on priorities and smooth collaboration. * Change management & adoption: Designed training and onboarding materials for recruiters and hiring teams to ensure adoption of AI solutions. Led workshops to facilitate understanding and trust in AI-driven recommendations. * Innovation & market watch: Conducted continuous monitoring of academic and technological advances in AI recruiting to refine methodologies and identify opportunities for improvement. Tech & tools: Python, SQL, LLM, RAG, Agile methodologies, stakeholder reporting frameworks.

• Subject: First data scientist hired to optimize revenue and design data-driven products, bridging analytics and product management. Owned the vision, roadmap, and execution of machine learning–powered initiatives (partner selection, GMV prediction, dynamic pricing, and experimentation) while collaborating with the Chief Revenue Officer (CRO), engineering, and business stakeholders to drive measurable impact: * Cross-functional leadership: Acted as Data Product Manager for data initiatives, defining product vision and roadmap, aligning stakeholders, and ensuring adoption of data products across the business. * Product discovery & partner evaluation: Designed and launched a machine learning product to assess new restaurant partners’ potential, reducing unqualified leads by 70% and increasing revenue per partner by up to 40% for new partners. * Dynamic pricing platform: Defined product strategy, led implementation, and ran multiple A/B test experiments across 2,000+ virtual restaurants. Transitioned pricing from static to dynamic models, boosting competitiveness and profitability. * Strategic pricing initiatives: Designed and implemented positioning-based pricing strategies, contributing to a cumulative 15% GMV uplift. * Experimentation platform: Conceived, scoped, and developed an internal experimentation product for scalable A/B testing. Solved key challenges in automated group splitting and fairness across restaurant cohorts. * Team building & leadership: Scaled the data science function by hiring a senior and junior data scientist. Provided mentorship, managed projects, and ensured delivery of high-impact initiatives. Tech: Python (Pandas, scikit-learn), SQL (BigQuery) , Looker, GCP

• Subject: Product Data Scientist supporting a driver-focused team leveraging data to unlock valuable insights and drive business impact across a range of topics. These include but are not limited to users behaviors segmentation, churn, UI/UX optimizations through A/B testing , fraud detection & debt reduction, pricing modeling using statistical modeling and Machine Learning. * Led multiple A/B test experiments to optimize user experience and user interfaces, resulting in approximately 4% increase in ride volume and greater driver awareness of debts * Conducted driver behavior segmentation and propensity modeling to enhance supply and balance the marketplace. * Modeled the impact of increasing ride prices in France (pricing) * Built a Master Id model that reduced sign-up fraud by over 10% and debts in African-based countries without negatively impacting the supply and demand Tech: Python (Pandas, scikit-learn, Tensorflow), SQL, Dataiku, Looker, AWS

Built and deployed a machine learning solution predicting bandwidth availability across OBS sites with < 6% error, driving smarter capacity planning and network reliability.