Machine Learning Lead (F/H) Dalma
Assurance santé pour chiens et chats avec une super app mobile.
Permanent
Paris, Berlin
A few days home
Salary: Not specified
> 4 years
5 years of study
Skills we're looking for
Autonomy
Business acumen
Communication skills
Collaboration and teamwork
Actuarial calculations
+2
You'll be part of
Paris, Berlin
50 employees
Application mobile
Assurance
Average age: 30
Founded in 2020
32%
68%
Lancée en avril 2021 par Alban de Préville, Raphaël Sadaka et Harry Belinga, Dalma est l’assurance santé pour chiens et chats qui connaît la croissance la plus rapide en France et en Allemagne 🚀
👉 Notre mission : être l’allié indéfectible des parents de chiens et chats gagas, passionnément dévoués. Nous souhaitons offrir du réconfort, des conseils, et une véritable protection à ceux que les animaux considèrent comme leur foyer.
Le ➕ : Une super app mobile qui simplifie les demandes de remboursements et permet à tous d’accéder à des conseils gratuits et illimités de vétérinaires.
Quatre ans après le lancement, Dalma c’est déjà :
✨ Plus de 60 000 chiens et chats protégés au quotidien
✨ Une levée de fonds de 20 millions d’euros en série B
✨ Ouverture de Dalma en Allemagne en octobre 2023
✨ Une équipe composée de 50 talents, en France et en Allemagne
✨ Une app notée 4,8 sur l’app store
You'll be working on
Dalma is a fast growing pet health insurer for dogs and cats in Europe.
We are building out our Insurance team and hiring a Machine Learning Lead to own the advanced modeling layer.
You will operate at the intersection of data, product and insurance, with direct impact on the growth and retention of our portfolio across France and Germany.
You will join the Insurance team and report directly to our Chief Insurance Officer (CIO).
The Insurance team is composed of:
Our CIO (currently being recruited)
A senior actuary
A team of two data analysts
You will also work closely with:
Our Product & Tech teams
Our founders
🎯 Modeling & pricing strategy
Design and deploy models that optimise our selling price from the actuarial pure premium, conversion and retention data
Build price elasticity and tariff segmentation models
Ensure the reliability and quality of data feeding into our pricing models
📈 Expanding the ML scope
Progressively extend your scope beyond pricing: churn prediction, claims operations prioritization, fraud detection
Become the go-to technical reference for all predictive modeling at Dalma
Own monitoring, retraining and long-term reliability of models in production
🤝 Cross-functional collaboration
Work closely with our actuary on claims data and pure premium assumptions
Translate the CIO’s strategic priorities into concrete model specifications
Collaborate with Product & Tech for model integration into production
Make complex quantitative topics accessible to non-technical audiences
We're looking for
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
Benefits
How we hire
Step 1: HR discovery call
Step 2: Interview with Raphaël, our COO
Step 3: Technical business case with our actuary and Raphaël
Step 4: Team fit
Step 5: Reference checks
Key figures
In short
Founding year
2020
Employees
50
Average age
30
Gender
68%
32%
