Career Opportunities: GERENTE ANALITICA Y CIENCIA DE DATOS (46747)The Chief Data and Analytics Officer (CDAO) is a leader responsible for leveraging the organization's data and analytics (D&A) assets to drive business value and achieve measurable outcomes. The CDAO's primary purpose is to ensure the organization utilizes its data strategically to inform decisions, enhance business operations, and foster innovation. This role involves establishing and executing a comprehensive data strategy, leading the D&A function, overseeing the development and implementation of data governance frameworks, and fostering a data-driven culture throughout the organization.
Minimum Requirements: A master's degree or Ph.D. in a relevant field such as data science, computer science, statistics, mathematics, business administration, or a related discipline is often preferred.Professional certifications in data science, analytics, or related areas can be advantageous.Extensive Experience in Data and Analytics: 10-15 years of experience in data management, business intelligence, analytics, and/or data science roles.5+ years of experience in Business Experience.Leadership Experience: Significant experience in leadership roles, including managing data and analytics teams and leading large-scale data projects.CPG Industry Knowledge: Experience in the CPG industry.Proficiency in Data Technologies: Expertise in data warehousing, data lakes, ETL (extract, transform, load) processes, and big data technologies (e.g., Hadoop, Spark).Advanced Analytics Skills: Strong knowledge of statistical analysis, machine learning, and predictive modeling techniques.Familiarity with BI Tools: Experience with business intelligence tools such as Microstrategy, Tableau, or Power BI.Programming Skills: Proficiency in programming languages commonly used in data science (e.g., Python, R, SQL).Business Strategy Alignment: Experience in aligning data strategy with business objectives and demonstrating the value of data-driven decision-making to stakeholders. Ability to conduct return on investment (ROI) analysis for data projects and initiatives.
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