Lead Data Scientist providing data science expertise and technical leadership for Caterpillar aftermarket parts forecasting. Managing complex analytics processes and ensuring accurate insights generation for critical business decisions.
About the role
- Data Scientist role at Mundiale, focusing on AI solutions and NLP technologies within a collaborative team environment. Responsibilities include model development and implementation.
Responsibilities
- Implement and test prompt engineering strategies, RAG and model integration in prototype and production environments.
- Build and evolve AI agents based on LLMs for automated customer support in chatbots.
- Develop, train and evaluate text classification models for intent recognition and other NLP use cases.
- Create data pipelines for preparing, cleaning, balancing and enriching textual datasets.
- Define and monitor performance metrics, performing statistical analyses for continuous model improvement.
- Work closely with Product, Engineering and Data Science teams to translate business needs into applied AI solutions.
Requirements
- Degree in Statistics, Data Science, Computer Science or related fields.
- Proficiency in Python programming and experience with libraries such as Pandas, Scikit-learn, Transformers and visualization tools (Matplotlib, Seaborn, Plotly).
- Knowledge of applied statistics and exploratory data analysis, including hypothesis testing, classification metrics and model validation.
- Experience training and evaluating classical classification models (logistic regression, tree-based models, etc.).
- Knowledge of NLP, with a focus on BERT and semantic representation techniques such as embeddings.
- Experience with LLMs, prompt engineering, AI agents and use of RAG architectures in customer service chatbots.
- Practical experience applying AI to products and automating conversational flows.
Benefits
- Flexible Benefit (allocate according to your needs: culture, ride-sharing/taxi app, subscriptions, gym, food, etc.)
- Unimed Unipart Health Plan
- Career development path
- Hybrid work
- Day Off
- Short Friday
- Collaborative and dynamic work environment
Job title
Job type
Experience level
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Not specified
Degree requirement
Tech skills
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