Senior Data Scientist

Location: Paris, Châtelet – Hybrid (2 days on-site / 3 days remote) Contract: Full-time (CDI) Team: Technology – Direct report to CTO 🧭 Main Mission Identify, design, and deploy AI and Machine Learning solutions that concretely increase the value delivered by the Mendo application to our users. As a Senior Data Scientist / AI Engineer, you will be the technical pioneer of AI integration into our product, with full autonomy to explore, experiment, and implement ML and GenAI models (fine-tuning, embeddings, RAG, etc.). Your mission: transform business opportunities into pragmatic and measurable AI solutions integrated in Mendo, serving over 60 enterprise clients (PwC Global, BDO, EY...). You will mentor a junior Data Scientist and establish the standards of excellence for data science practice at Mendo. 🛠️ Key Responsibilities 1. Proactive AI Opportunity Identification Be constantly on the lookout: analyze the product, usage patterns, and customer feedback to identify where AI can create concrete value. Propose relevant AI use cases aligned with product roadmap and business objectives. Ruthlessly challenge and prioritize AI initiatives: absolute focus on user impact and ROI. Collaborate closely with the Product Lead and PMs to transform business needs into actionable AI opportunities. Establish a framework for prioritizing AI projects based on impact, feasibility, and effort. 2. Model Research, Development, and Deployment Research and experiment with ML and GenAI models (LLMs, embeddings, classification, clustering, recommendation). Fine-tune existing models (OpenAI, Anthropic, open-source) rather than building from scratch. Design and implement end-to-end AI pipelines: data prep, training/fine-tuning, evaluation, deployment. Develop RAG (Retrieval-Augmented Generation), semantic search, and other relevant GenAI architecture solutions. Optimize model performance and costs in production (latency, tokens, infrastructure). Implement monitoring and continuous quality evaluation systems for models. 3. Ruthless Pragmatism and Efficiency Prioritize ruthlessly: know when to say no to "cool" AI projects without real impact. Favor simple and effective solutions: avoid over-engineering and POCs that lead nowhere. Iterate quickly: prototype fast, test with real users, measure impact, and pivot if necessary. Maintain constant balance between exploration (R&D) and execution (value delivery). Document technical decisions and trade-offs clearly and concisely. 4. Technical Leadership and Mentoring Mentor and train a junior Data Scientist: share your expertise, define growth objectives, and delegate effectively. Establish data science and AI engineering best practices at Mendo (code quality, MLOps, experimentation). Collaborate closely with development squads to integrate models into the product. Evangelize AI possibilities internally and educate product and business teams. Progressively build the data science practice at Mendo in preparation for team growth. 5. Cross-functional Collaboration Work hand-in-hand with the CTO to align AI strategy with overall technical vision. Collaborate with product teams to understand user pain points and imagine AI solutions. Coordinate with development teams to ensure smooth integration of models into production. Interact with Customer Success teams to understand real usage and measure AI feature impact. Regularly present your results and recommendations to stakeholders (product, sales, leadership). 🧩 Required Skills Knowledge & Technical Expertise Machine Learning expertise: minimum 4-6 years of experience in ML model development and deployment. Deep mastery of LLM fine-tuning (OpenAI, Anthropic, Llama, Mistral, etc.). Solid experience with GenAI architectures: RAG, embeddings, semantic search, advanced prompt engineering. Knowledge of ML/DL frameworks: PyTorch, TensorFlow, Hugging Face Transformers, LangChain, LlamaIndex. Experience with cloud platforms for ML (Azure ML, AWS SageMaker, or Google Vertex AI). Python mastery and data science libraries (scikit-learn, pandas, numpy, etc.). Knowledge of vector databases (Pinecone, Weaviate, Qdrant, etc.). Familiarity with MLOps pipelines: model versioning, A/B testing, production monitoring. Understanding of cost, latency, and scalability challenges for AI solutions in production. Know-how Ruthless pragmatism: demonstrated ability to prioritize effectively and deliver value quickly. Opportunity identification: track record of AI use case proposals that created measurable business impact. End-to-end ownership: experience from research through deployment and production monitoring. Ability to prototype rapidly and iterate based on user feedback. Excellence in model evaluation and benchmarking (metrics, rigorous experimentation). Clear communication of complex technical concepts to non-technical audiences. Experience in close collaboration with product and engineering teams. Ability to mentor and train more junior profiles. Soft Skills Product mindset: obsession with user impact and real value creation, not just tech "coolness". Autonomy and proactivity: ability to identify opportunities without waiting to be told. Pragmatism and efficiency: preference for simple solutions that work over over-engineering. Sharp sense of priorities: courage to say no to projects without clear impact. Insatiable curiosity: passion for new AI advances and constant desire to learn. Scientific rigor: methodical approach to experimentation and benchmarking. Team spirit: ability to collaborate effectively with product, engineering, and business. Teaching ability: pleasure in sharing knowledge and helping others grow. Alignment with our values: Learning, Innovation, Excellence, Kindness. 🎓 Desired Profile Minimum 4-6 years of experience in data science / ML engineering with focus on production deployment. Significant experience with LLMs and GenAI architectures (fine-tuning, RAG, embeddings). Demonstrated track record of AI projects that created measurable business value in product environments. Experience in B2B or B2C SaaS with millions of users is a strong plus. Proven ability to work autonomously and make informed technical decisions. Excellent command of English (technical and professional). French is optional but appreciated. Experience in tech education, learning, or productivity tools is a plus. PhD in ML/AI, Computer Science, or related field is a plus but not required. 📈 What We Offer Equity: participation in a fast-growing scale-up's capital. Major impact: be the AI pioneer at Mendo and shape the product's future. Total autonomy: freedom to explore, experiment, and propose AI initiatives. Direct reporting to CTO: visibility and influence on the company's technical strategy. Rapid evolution: opportunity to build and lead the AI/ML team as the company grows. Cutting-edge environment: work at the heart of generative AI with access to latest technologies. Stimulating work environment: young, fun, and caring culture where innovation is encouraged. Flexibility: hybrid model 2 days/3 days remote for optimal work-life balance. Meaningful mission: contribute to making AI accessible and impactful for everyone. 🚀 About Mendo At Mendo, we combine our passion for technology with a commitment to learning. Our mission? Make generative AI accessible to everyone. Through an integrated and gamified software platform, we make understanding and using generative AI simple and impactful. Technology Pioneers – We believe humans have a vital role in this technological revolution. 🎯 Why This Role is Unique Joining Mendo as the first Senior Data Scientist / AI Engineer is a rare opportunity: Exceptional playground: work on an AI product to teach AI – the ultimate meta-recursion Innovation freedom: carte blanche to identify and implement high-impact AI use cases. Immediate impact: your models will reach tens of thousands of users in the world's largest companies. Build from scratch: establish the foundations of AI/ML practice at Mendo and recruit your future team. No AI bullshit: culture of ruthless efficiency where only user impact matters, not buzzwords. What we expect from you: a senior autonomous profile who doesn't just execute tickets but proactively identifies where AI can transform our product. Someone who knows how to say "this project doesn't make sense" as much as "here's a golden opportunity we must seize". A passionate pragmatist who prefers delivering 3 simple AI features that work rather than a complex POC that stays in a notebook. #J-18808-Ljbffr