Senior Data Scientist | Descartes & Mauss · Teeming.ai
Descartes & Mauss
Descartes & Mauss is a Paris-based SaaS company offering the first AI-powered growth strategy platform designed to help businesses make better, faster decisions and accelerate growth. Their platform…
Descartes & Mauss is a Paris-based SaaS company offering the first AI-powered growth strategy platform designed to help businesses make better, faster decisions and accelerate growth. Their platform…
Headquarters: Paris (registered as DESCARTES & MAUSS, SAS)
Product: AI-powered growth strategy SaaS for scenario planning, systemic modeling, and strategic foresight
Founded: 2021
Team size: ~28 employees
Latest funding: €5.5M round (lead investors: Elaia, Polytechnique Ventures, announced June 2024)
Company Overview
Problem Domain
Strategic planning, growth strategy, scenario modeling, and go-to-market optimization
Founded
2021
Industry
Software Development
Tech Stack
Cloudflare
Cloudflare CDN
Cloudflare Hosting
Common Crawl
Envoy
DNSSEC
IPv6
Funding Track Record
Venture- 2024-06-12
€5.5M
Announced on company site
Investor Signal
“Elaia and Polytechnique Ventures as lead investors”
Founders
What we do
Join the Team
Senior Data Scientist
On-SiteParis, FR
On-Site • Paris, FR
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We are seeking an exceptional Data Scientist with deep expertise in advanced AI systems, particularly in the design, deployment, and optimisation of Large Language Models (LLMs) beyond standard usage patterns
The ideal candidate will have hands-on experience with Agentic AI architectures, a solid understanding of AGI-oriented research, exceptional mathematical foundations, and a keen ability to identify and model emerging growth spaces
5+ years in Data Science, Machine Learning, or Applied AI
Strong understanding of NLP, deep learning architectures (Transformers, RNNs, etc.), and generative AI
Proficiency with Python and ML frameworks (PyTorch, TensorFlow, JAX)
Hands-on with open-source and proprietary LLMs (e.g., LLaMA, GPT, Claude, Mistral, Gemini, etc.)
Experience building autonomous agents with frameworks like LangChain, CrewAI, AutoGPT, or custom architectures
Familiarity with multi-agent coordination and reasoning frameworks
Experience with graph databases (Neo4j, AWS Neptune) and vector stores (Pinecone, Weaviate, Milvus, FAISS)
Strong SQL and NoSQL skills, and experience with data pipelines for large-scale ingestion and processing
Understanding of distributed systems and cloud platforms (AWS preferred)
Strong background in applied mathematics, statistical modelling, and optimisation
Ability to create and validate complex models with explainability in mind
Familiarity with Bayesian methods, time-series forecasting, and graph theory
Ability to translate technical findings into strategic opportunities
Familiarity with innovation trend analysis, market research, and opportunity mapping
Published research in AI, NLP, or AGI-related domains
Contributions to open-source AI frameworks or libraries
Experience in multi-modal AI (vision, speech, and text integration)
Familiarity with knowledge graph embeddings and semantic reasoning
Exposure to reinforcement learning for autonomous decision-making
Comfort working in fast-paced, experimental environments with evolving priorities
What the job involves
You will work at the intersection of AI research, applied machine learning, and strategic data-driven opportunity discovery—helping shape solutions that push the boundaries of intelligent systems
Develop, fine-tune, and evaluate LLMs for specialised tasks (beyond prompt engineering)
Build retrieval-augmented generation (RAG) pipelines with scalable vector/graph data structures
Optimise models for performance, interpretability, and efficiency
Integrate LLMs with structured and unstructured data sources
Design and implement multi-agent systems capable of goal-oriented reasoning and long-term planning
Build dynamic tool-using agents that can orchestrate APIs, databases, and knowledge graphs autonomously
Research and implement advanced memory, planning, and decision-making frameworks for AI agents
Contribute to AGI-related experiments, focusing on reasoning, adaptability, and generalisation
Prototype cognitive architectures for open-ended problem-solving
Explore novel algorithms in reinforcement learning, self-improvement loops, and emergent behaviours
Apply advanced mathematical methods (linear algebra, optimisation, probability theory, graph theory, and statistics) to complex AI challenges
Design robust evaluation metrics for intelligent systems
Implement mathematical models for simulation, forecasting, and optimisation in AI pipelines
Use advanced analytics and AI-driven market mapping to identify high-potential domains
Develop predictive models for emerging trends using cross-domain datasets
Collaborate with strategy teams to translate AI insights into business and innovation roadmaps
The application process
30 mins chat with HR team
30 mins chat with the hiring manager
A Case Study
Office tour & meet the team (if you’re Paris based) - if your team is based in Paris, we’d love to invite you to our office for a quick tour and to meet them in person!
