Data Science and Analytics Leader with 20+ years experience and a deep commitment to leveraging data to create meaningful impact.* Extensive experience applying statistical analysis, AI, machine learning, and data-driven decision making to optimize operations and solve complex business challenges. * Spearheaded projects involving dimensionality reduction (PCA), K-means, and DBSCAN clustering algorithms for tasks like stock pair identification for statistical arbitrage, enhancing forecasting accuracy, and delivering actionable insights.* Demonstrated ability in feature engineering, developing and refining predictive models, and applying stochastic optimization to improve business outcomes. Skilled in Python, R programming, ETL pipelines, and deploying models through cloud computing (AWS).* Experience working with Causal Inference, Bayesian networks, Neural Networks, Deep Learning, LLMs, and NLP and eager to use these tools to innovate and explore new AI and machine learning methods for enhancing decision-making processes.* Proven track record in implementing agile methodologies, scaling data science operations, developing product roadmaps, and deploying machine learning models in real-time environments. Collaborative leadership style with a focus on mentoring and team building. * Interests: Piano, Science Fiction, Spanish Language, Theoretical Physics, Cosmology, Consciousness, Emergence, RealityTechnical skills:* Explainable AI: SHAP, Decision Trees* Optimization: LP, MILP, SLS (stochastic local search), CPLEX, Gurobi* Dimensionality reduction (PCA, t-SNE, MDS)* Deep learning (TensorFlow / Keras). NLP, CNNs, Transfer Learning* Bayesian network analysis, Causal inference* AI for Medicine: Survival Analysis, Image Processing, Unstructured data* R, Python, C++, MATLAB, SQL, Docker, AWS