- Company Name
- Leonar
- Job Title
- Consultant(e) Data Scientist / AI Engineer
- Job Description
-
**Job Title**
Data Scientist / AI Engineer Consultant
**Role Summary**
Deliver end‑to‑end data and AI consulting services for diverse industry clients. Lead the full project lifecycle from data scoping and collection to model development, deployment, and monitoring. Build and integrate advanced ML/LLM models and AI agents, and develop robust data pipelines. Communicate insights and business value to stakeholders and support continuous R&D and knowledge sharing.
**Expectations**
- Execute projects across multiple sectors, delivering innovative solutions (ML forecasts, AI agents, monitoring tools).
- Operate autonomously, with clear documentation, proactive communication, and initiative.
- Showcase measurable impact and business value of delivered solutions.
**Key Responsibilities**
- Define and scope data collection requirements; clean, preprocess, and transform data.
- Develop ML/DL models and LLM‑based solutions tailored to client problems.
- Integrate AI agents (autonomous agents, LLM orchestrators, intelligent action chains) into operational contexts (automation, copilots, RAG).
- Build and maintain data pipelines: ingestion, preprocessing, transformation, and exposure to use‑cases.
- Visualize results and communicate findings to business stakeholders.
- Coordinate project progress and articulate value propositions.
- Participate in R&D: create internal tools, libraries, and evolve the in‑house AI platform.
- Contribute to knowledge sharing, documentation, and technical watch.
**Required Skills**
- Cloud infrastructure (GCP, Azure, or AWS) and containerization (Docker).
- Data pipeline engineering, Data Lake/Data Warehouse management.
- ML Engineering, ML/Deep Learning, LLMs, AI agents.
- Programming: Python, SQL, Git.
- Experience with orchestration/agent frameworks (LangChain, LangGraph, Dify, n8n).
- API‑driven web technologies (FastAPI, Flask, Django) and visualization frameworks (Streamlit, Dash).
- Strong autonomy, clarity, pedagogy, initiative, and organizational skills.
**Required Education & Certifications**
- Master’s degree or equivalent Grande École engineering background in Data Science, AI Engineering, or related field.
- Demonstrated experience in at least one of the following areas: cloud infrastructure, data pipeline implementation, Data Lake/Data Warehouse, ML Engineering, Machine Learning/Deep Learning, LLMs, AI agents.