Machine Learning Lead (F/H)

Join Dalma, a fast-growing pet health insurer in Europe, as a Machine Learning Lead. In this role, you will design and deploy models to optimize pricing, expand the scope of machine learning applications, and collaborate cross-functionally with various teams. You should have at least three years of experience in machine learning or data science, strong technical skills, and a strong business sense. Fluency in English is required, and knowledge of French or German is a plus.

• Concevoir et déployer des modèles qui optimisent notre prix de vente à partir de la prime pure actuarielle, des données de conversion et de rétention.
• Étendre progressivement votre champ d'application au-delà de la tarification : prédiction de l'attrition, priorisation des opérations de réclamation, détection de la fraude.
• Travailler en étroite collaboration avec notre actuariat sur les données de sinistres et les hypothèses de prime pure.

**Must have**

• **Experience:** At least three years in Machine Learning/ Data science — you have owned an ML model end-to-end, from exploration to production
• **Sector**: Insurance preferred, but fintech, retail banking, e-commerce/marketplace, or telecom/SaaS B2C also relevant
• **Technical skills**: Strong expertise in statistical modeling and ML (logistic regression, survival models, clustering, etc.) — Python proficient, R a plus; fluent SQL; comfortable with a BI tool
• **Business sense**: Strong business appetite; able to translate a technical model into an actionable decision
• **Autonomy**: Full ownership from exploration → model → production → monitoring
• **Communication**: Strong communicator, able to make quantitative topics clear to non-technical stakeholders
• **Curiosity**: Eager to grow your scope beyond pricing over time
• **Languages**: Fluent English required; French or German a plus
• **Location**: Local contract (Paris, Berlin), or fully remote work is possible (with regular trips to the Paris headquarters—about once a month)

**Nice to have**

• **Insurance literacy**: good understanding of insurance KPIs (loss ratio, retention rate, LTV)
• **Active use of AI tools** (LLMs, Copilot) to accelerate modeling and coding