{"id":2007757,"url":"https://alion.io/job/vademi-data-scientist-parcours-client-attribution-recommandation-llm-python-snowflake-dataiku","title":"Data Scientist Parcours Client – Attribution, Recommandation & LLM (Python / Snowflake / Dataiku)","company":{"id":3908423,"name":"Vademi","domain":"vademi.com","url":"https://alion.io/company/vademi","size_band":"11-50","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":null,"employment_type":"freelance","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Marseille, France"],"countries":["FR"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":44000,"max_usd":77000,"period":"year","method":"role_country_seniority_unknown","sample_n":151},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Embeddings","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"NLP","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"Recommender Systems","optional":false},{"name":"Snowflake","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-09-30T09:40:49Z","employer_posted_date":null,"last_verified_at":"2026-09-30T09:40:49Z","board_verified":false,"closed_at":null,"days_open":12,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":12},"description":"Au sein du pôle digital d'un grand groupe international, vous rejoignez l'équipe d'optimisation des parcours clients digitaux dans le cadre de son renforcement. L'objectif est de développer des modèles analytiques avancés pour optimiser les parcours clients, améliorer la conversion, personnaliser l'expérience digitale et maximiser la performance des actions marketing et opérationnelles.\nVous interviendrez au cœur des sujets clés de l'équipe :\nClustering et segmentation comportementale : segmenter les utilisateurs selon leur navigation, leurs transactions et leurs usages digitaux, et identifier personas, micro-segments, intentions et points de friction.\n\nSystèmes de recommandation : concevoir des recommandations personnalisées de contenus et de services additionnels selon une approche hybride (collaborative, contenu et séquentielle).\n\nModèles prédictifs : prédire la conversion, le churn et la complétion du funnel, prévoir les volumes par étape du parcours et classifier les comportements (drop-off, intention, scoring).\n\nAttribution multi-touch : construire des modèles de Markov (1er et 2e ordre) et de Shapley, mesurer le poids de chaque point de contact (email, WalkMe, AB Tasty, notifications, pages clés) et calculer le ROI des actions menées.\n\nIA générative et LLM : développer des modèles capables d'interpréter automatiquement les résultats analytiques, de détecter les irritants et de générer des recommandations pour orienter les décisions.\nCOMPÉTENCES TECHNIQUES ATTENDUES\nLangages : Python avancé (programmation orientée objet), SQL.\n\nData platform : Snowflake, Dataiku DSS (scénarios, job scheduling), notebooks Jupyter.\n\nMachine learning : supervisé et non supervisé (K-means…), deep learning, séries temporelles, feature engineering, SHAP.\n\nModélisation marketing : attribution multi-touch (Markov, Shapley), recommender systems, scoring, prédiction de conversion et de churn.\n\nIA générative : LLM, NLP, embeddings, classification sémantique.\n\nProfil recherché\nData Scientist confirmé(e), vous avez déjà appliqué le machine learning à des problématiques de comportement utilisateur, de parcours client ou de marketing digital. 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