- Company Name
- HeadMind Partners
- Job Title
- Consultant Data Scientist
- Job Description
-
Job title: Consultant Data Scientist
Role Summary:
Drive end‑to‑end data science solutions for enterprise clients (CAC40 & SBF120). Act as a consultant, translating business needs into data‑driven models and guiding clients on interpretation and adoption. Work closely with cross‑functional teams to deliver AI solutions in NLP, Computer Vision, and AI‑for‑Operations domains, while contributing to internal R&D and technology scouting.
Expectations:
- Own the specification and delivery of client‑centric AI projects.
- Provide clear, actionable insights and recommendations to non‑technical stakeholders.
- Stay current with cutting‑edge AI technologies, especially generative models, and integrate them into production pipelines.
- Collaborate with data engineers, full‑stack developers, and research scientists to scale solutions.
Key Responsibilities:
- Explore and preprocess client data to uncover problem context.
- Design and implement ML/DL pipelines: XGBoost, Transformers, LLMs, MLLMs for NLP (classification, compliance, RAG, fine‑tuning), Computer Vision (image recognition, generation, deep‑fake detection), and AI‑for‑Operations (time‑series forecasting, process optimization, predictive maintenance).
- Evaluate model performance, conduct hyper‑parameter tuning, and propose iterative improvements.
- Lead R&D initiatives in generative AI, including fine‑tuning and deployment of LLMs (GPT, Falcon, Llama).
- Maintain a state‑of‑the‑art knowledge base, perform continuous technology scouting, and share findings with the team.
- Deliver client workshops and training sessions to facilitate adoption of AI solutions.
Required Skills:
- Proficiency in Python with TensorFlow/PyTorch and experience building production ML pipelines.
- Expertise in deploying LLMs using Hugging Face Transformers, OpenAI, and LangChain.
- Familiarity with ElasticSearch, cloud platforms (AWS, GCP, Azure), and MLOps/AIOps tooling (CI/CD, CUDA, GPU optimization).
- Strong analytical mindset, data exploration, feature engineering, and model evaluation skills.
- Excellent communication and ability to translate complex technical concepts for business audiences.
Required Education & Certifications:
- Graduate from a top engineering school (e.g., CentraleSupélec, ENSAE, École Polytechnique, Supaero, ENSTA) or hold a PhD in quantitative science or Artificial Intelligence.
- Dual engineering/commercial degree or equivalent advanced quantitative training is preferred.
- Demonstrated certifications in data science or cloud platforms (AWS Certified Machine Learning, GCP Professional Data Engineer, Azure Data Scientist Associate) are a plus.