Mario Sanchez

• Designed and implemented data solution strategy treating data as a product.
  Aligned multiple data domains with business objectives, enhancing cross-functional collaboration.
  Developed scalable and reusable data products delivering tangible business value.
  Spearheaded creation of data solution framework compliant with global digital standards.
  Ensured integrated approach to data management within Clean Energy at AES Renewables.
  Championed culture of shared data ownership across AES Renewables businesses.
  Established best practices for data product development, ensuring high-quality solutions.
  Monitored effectiveness of data mesh strategy, implementing iterative improvements.

• Led initiatives that fostered data-centric culture across Operations to support informed decision-making.
  Oversaw development of AI/ML solutions by a dedicated team, improving T&D Operations effectiveness.
  Collaborated with direct reports to establish goals and assess execution strategies.
  Articulated complex analytical findings in an accessible manner for varied audiences.
  Executed process improvements that increased operational efficiency and reduced barriers.
  Facilitated mentorship programs, enabling professional growth and enhancing solution scalability.
  Strengthened analytics adoption through cross-functional leadership in data knowledge sharing.
  Projected future resource needs for T&D Operations to design responsive solutions.

Within the responsibilities of the role were:
• Develop new and innovative analytical solutions that meet customers’ requirements and needs for financial businesses, retailers and Telcos
• Lead cross-functional projects using advanced data modelling and analysis techniques to discover insights that will guide strategic decisions and uncover optimization opportunities
• Examine, interpret and report results of analytical initiatives to stakeholders in leadership, technology, sales, marketing and product teams
• Lead analytical teams in the design and creation of predictive and decision models to be deployed in production systems, or for research. This includes participating in analysis of large amounts of historical data, determining suitability for modeling, pattern identification and variable creation, selection of sampling criteria, generating performance definitions and variables, performing experiments with different types of algorithms and models, and analyzing performance to identify the best algorithms to employ.
• Coordinate or support the implementation, post-implementation and model maintenance.
• Lead client-facing meetings, seminars, and workshops to increase EFX solutions
comprehension and market positioning.

Credit business data science specialist, within the responsibilities of the role were:
• Build and tune scoring models for origination, behaviour, collection and recovery
• Build and evaluate predictive and decision models to be deployed in production
systems, or for research. This includes participating in analysis of large amounts of
historical data, determining suitability for modeling, pattern identification and variable
creation, selection of sampling criteria, generating performance definitions and
variables, performing experiments with different types of algorithms and models, and
analyzing performance to identify the best algorithms to employ.
• In charge of implementation, post-implementation and model maintenance support.

Food, home, and personal care industry trade marketing executive (commercial and sales area). The responsibilities of the position included: • Data-Driven Strategy Development: Utilize Nielsen’s comprehensive data and analytics to develop and implement effective trade marketing strategies that enhance brand visibility and drive sales growth.
• Market Analysis: Conduct in-depth market analysis to identify trends, opportunities, and competitive insights for customers in the different distribution channels and categories.

• Performance Tracking: Monitor and analyze the performance of trade marketing initiatives using data analytics to measure KPIs, and optimize future campaigns.
• Cross-Functional Collaboration: Work closely with sales, product, and data science teams to ensure seamless execution of marketing strategies, and data integration.
• Client Engagement: Engage with key clients to understand their needs, and provide data-driven insights and recommendations to enhance their market performance.
• Reporting and Insights: Prepare detailed reports and presentations on trade marketing activities, providing actionable insights based on data analysis.
• Propose improvement opportunities based on market behavior within each of the categories and countries, aligned with the regional and global brand strategy of the customer.
Manage quality issue reports for the regional (LATAM) and global strategic planning team based in London, UK.