• Data Science Project Management: Efficiently coordinating data analysis initiatives for large-scale clients, focusing on customized analytical solutions that meet specific business needs and industry challenges.• Client-Oriented Data Strategy: Developing and implementing data strategies based on machine learning and advanced analytics, aligned with clients' commercial and operational objectives.• Client and Stakeholder Relations: Building and maintaining collaborative relationships with high-level clients, ensuring clear communication and strategic alignment for the effective integration of data solutions.• Data Science Skills Development and Updating: Leading the team in continuous updating of emerging technologies and advanced data science practices, ensuring project delivery that yields significant results and added value for clients.

• Technical Leadership in Data Science: Oversee data analysis projects, ensuring the delivery of effective and innovative solutions, aligned with specific client demands and consultancy objectives.• Development of Analytical Solutions: Create and implement machine learning models and statistical analyses, focusing on generating valuable insights and practical solutions for complex client challenges.• Collaboration with Project Teams: Work closely with data engineering teams, analysts, and business experts to ensure integrated and efficient approaches in data science projects.• Team Training and Mentorship: Guide and develop the technical and analytical skills of the data science team, fostering an environment of continuous learning and innovation.

• Machine Learning Model Development: Build and optimize predictive models and machine learning algorithms to address specific client problems and generate valuable insights.• Data Analysis and Insights: Conduct statistical and exploratory analysis on large datasets, transforming them into actionable information that supports business decision-making.• Collaboration with Multidisciplinary Teams: Work alongside data engineers, analysts, and business experts to integrate data science into business strategies and IT solutions.• Results Communication: Effectively present analysis and model findings to internal stakeholders and clients, ensuring insights and recommendations are understood and applied.

• Development and Implementation of Analytical Solutions: Build and enhance machine learning models and data analyses for applications, focusing on innovative solutions to improve customer experience.• Automation and Process Optimization: Develop and deploy RPA (Robotic Process Automation) systems for automating administrative processes and web scraping of public market data, generating cost savings and relevant information for competitiveness.• Clear Communication of Insights: Present data findings in a clear and understandable manner to non-technical teams, facilitating the understanding and application of analytical insights in financial decisions.

Development of scientific research in the area of quantum mechanics, using MATLAB software for data analysis and LaTeX for writing articles.

Teach classes in physics, chemistry and mathematics for students from elementary to high school.

Teach classes in physics and mathematics, with high school content, focused on pre-university students.