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Dans le cadre du remplacement d’un consultant senior sortant, tu rejoindras l’équipe Pricing & Revenue Management afin d’assurer la continuité, l’évolution et la fiabilisation des modèles algorithmiques stratégiques. Ton rôle sera clé pour concevoir, développer et optimiser des modèles avancés de pricing et de revenue management, permettant de prévoir, indexer et optimiser les contrats clients dans un contexte business à forts enjeux. 🧠 Missions principales 1. Développement & optimisation de modèles Concevoir et développer des modèles avancés de pricing (indexation, forecasting, optimisation des revenus). Améliorer la performance des algorithmes existants (précision, vitesse, robustesse, explicabilité). Construire de nouveaux modèles data-driven liés au revenue management (élasticité, stratégie tarifaire, scénarios). 2. Engineering & Data Pipeline Développer, maintenir et optimiser des pipelines dans Azure Data Factory & Azure Databricks . Manipuler, transformer et structurer des données dans un environnement big data. Intégrer et orchestrer les données via Azure Lakehouse / ADLS . (Bonus) Utiliser PySpark pour gérer des volumes de données importants. 3. Collaboration & Interaction Business Travailler en étroite collaboration avec les équipes Pricing, Finance et Opérations. Comprendre les besoins business et les traduire en modèles statistiques exploitables. Documenter, présenter et vulgariser les résultats auprès des équipes métier. Garantir une forte réactivité et la fiabilité des livrables compte tenu des enjeux stratégiques. 🛠️ Stack technique Python : indispensable (modélisation, data processing, industrialisation). Azure Cloud : Databricks, ADF, ADLS / Lakehouse. PySpark : apprécié. Méthodes & domain expertise : Pricing algorithmique Revenue management Forecasting (séries temporelles, modèles ML) Optimisation (linéaire, stochastique, contraintes)

Senior Data Scientist - Asset Risk Modelling London - Hybrid, 3 days in office £85,000 - £90,000 + Bonus + Great Pension + Private Healthcare + 28 days Holiday + Hybrid Working This is a brilliant opportunity for a Senior Data Scientist with strong experience in model risk management, pricing, and insurance to join a market-leading organisation during a key period of growth and innovation. The Asset Risk function is responsible for forecasting key financial risks such as Residual Value, SMR, Insurance Lease Pricing, Economic Capital, and Customer Pricing. As part of their continued expansion, they are now seeking a talented Senior Data Scientist to join the Asset Risk Modelling Team and help shape the future of their modelling capabilities. In this role, you will take ownership of developing, maintaining, and enhancing advanced forecasting and pricing models that underpin critical business decisions. Working closely with the Modelling Manager and wider stakeholders, you'll ensure the robustness and transparency of all models, while continuously improving methodologies, data use, and analytical processes. You will also play a key role in delivering the model risk management framework across the Asset Risk function. The ideal candidate will be an experienced Data Scientist/Quantitative Modeller with a strong technical background in Python, R, or similar tools, and proven experience in model development within pricing, insurance, or financial risk. You'll combine deep technical expertise with strong business understanding, communicating insights effectively to both technical and non-technical audiences. A fantastic opportunity to join a forward-thinking organisation where you'll have genuine influence, work on high-impact projects, and develop your career within a collaborative and progressive environment. The Role: Develop, implement, and maintain advanced statistical and machine learning models for pricing and risk forecasting Support the delivery and enhancement of the model risk management framework within the Asset Risk function Collaborate with business SMEs to align model outputs with strategic objectives and ensure transparency in assumptions and methodologies Provide technical guidance on data, modelling techniques, and analytical best practices Lead the continuous improvement of modelling tools, documentation, and governance standards Work closely with cross-functional teams across Asset Risk, Product, and Data to ensure consistent and efficient delivery The Person: Proven experience as a Senior Data Scientist, Risk Modeller, or similar role Strong technical skills in Python, R, or equivalent for statistical modelling and forecasting Experience within insurance, pricing, or financial risk environments Excellent understanding of model risk management principles and governance Strong communication skills with the ability to explain technical outputs to senior stakeholders Comfortable working in a hybrid model, 3 days per week in the London office

Vous êtes un Data Scientist expérimenté, spécialisé dans l'IA générique et Python ? Emagine vous offre l'opportunité de guider et de diriger le développement de structures et d'outils efficaces afin de créer des applications d'IA fiables et dignes de confiance dans un environnement bancaire international. Are you an experienced Data Scientist with expertise in Gen AI and Python? Emagine has an opportunity for you to guide and lead the development of effective structures and tools to create reliable, trustworthy AI applications within a global banking environment. As part of an AI-focused emagine team working on Gen AI initiatives that leverage LLMs and advanced techniques to solve complex business problems. You will work on unstructured data from sources such as legal documents and financial trading policies, building solutions that enable accurate and reliable outcomes. Main Responsibilities Lead the design and implementation of Gen AI solutions for text-based and LLM-driven use cases. Develop Python-based tools for data ingestion, modelling, and manipulation of large volumes of unstructured data. Define effective structures and frameworks to ensure reliability and trustworthiness in AI applications. Collaborate with legal and compliance teams to process and model complex datasets. Key Requirements 5+ years of experience in Data Science including international corporate environments. Strong expertise in Python and hands-on experience with LLMs (e.g., Lama 7DB, GPT-4 API). Familiarity with vectorization, chunking, and advanced data modelling techniques. Knowledge of tools such as PySpark, MongoDB, graph databases, SparkleDP. Self-driven, proactive, and comfortable working in a fast-paced environment. Nice to Have Exposure to legal or procedure-focused applications. Other Details Work is a minimum of 3 days per week on-site (8th). Apply with your latest CV or reach out to Brendan to find out more.