- Statistical analysis, data visualization.

- Predictive Analytics: Regression analysis, time series forecasting, classification techniques, market mix modeling

- Prescriptive Analytics: Optimization, simulation modeling.

- Text Analytics: Natural Language Processing (NLP), sentiment analysis.

Extensive knowledge of machine learning techniques, including :

- Supervised Learning: Linear regression, logistic regression, decision trees, support vector machines, random forests, gradient boosting machines among others

- Unsupervised Learning: K-means clustering, hierarchical clustering, principal component analysis (PCA), anomaly detection among others

- Reinforcement Learning: Q-learning, deep Q-networks, etc.

- Experience with Generative AI and large language models (LLMs) for text generation, summarization, and conversational agents.

- Researching, loading and application of the best LLMs (GPT, Gemini, LLAMA, etc.) for various objectives

- Hyper parameter tuning

- Prompt Engineering

- Embedding & Vectorization

- Fine tuning

- Proficiency in data visualization tools such as Tableau or Power BI.

- Strong skills in data management, structuring, and harmonization to support analytical