Colombia
Strategic leader in Marketing Effectiveness and Analytics with over seven years of experience bridging the gap between financial strategy and technical innovation. Holding a Master’s degree in Analytics and currently pursuing an MBA, I specialize in transforming complex data ecosystems into profitable business decisions. Currently, I lead Marketing Effectiveness initiatives focused on maximizing ROI through advanced Marketing Mix Modeling (MMM) and AI-driven Social Listening. My expertise combines deep technical proficiency in Machine Learning, Python, and AWS with a strategic financial vision to optimize media spend and drive consumer-centric growth. I am dedicated to empowering high-performing teams and establishing a data-driven culture that aligns technical execution with corporate objectives.
Skills: Marketing Strategy · Marketing Mix Modeling (MMM) · ROI Optimization · Social Listening · Machine Learning · Consumer Insights · Data Strategy · Python · Artificial Intelligence · Financial Analysis Responsibilities: · Strategic leadership of marketing effectiveness initiatives, overseeing the implementation of Marketing Mix Modeling (MMM Lite) to measure elasticity and maximize Return on Investment (ROI) across media channels. · Design and deployment of AI-driven Social Listening systems utilizing Machine Learning and NLP to automate sentiment analysis and reputation management in real-time. · Orchestration of a unified data ecosystem, integrating complex data sources (Sales, Media, Digital) to provide a "single source of truth" and agile visualization for Brand Management teams. · Translation of advanced predictive models and technical insights into actionable commercial strategies, ensuring full alignment between data capabilities and financial business objectives. · Collaboration with Finance and Marketing stakeholders to drive a data-driven culture, optimizing budget allocation and enhancing consumer understanding through advanced analytics.
Skills: AWS · Snowflake · Python · Amazon SageMaker · Large Language Models · MLOps · Machine Learning · Data Science · SQL · Leadership · Team Management Responsibilities: · Strategic leadership of the Advanced Analytics and Data Science team, defining the digital transformation roadmap and establishing best practices in AI and ML. · Design and implementation of Large Language Models (LLM) and advanced AI solutions to optimize business processes and enhance decision-making capabilities. · Management and optimization of cloud infrastructure in AWS, including MLOps pipeline development and model deployment in production using SageMaker. · Direction of advanced analytics initiatives, overseeing the development of predictive and prescriptive models to drive business growth. · Collaboration with key stakeholders to identify AI and ML application opportunities, aligning analytical strategy with business objectives. · Development and mentoring of the analytics team, fostering innovation and adoption of new technologies in AI and data science.
Skills: AWS · Snowflake · Python · SQL · Machine Learning · Data Analytics · Power BI · Tableau · Data Visualization · Business Intelligence · Data Modeling · Stakeholder Management Responsibilities: · Leadership and execution of analytics and business intelligence initiatives, providing data-driven insights to support decision-making processes. · Design and implementation of predictive and descriptive analytics models to identify trends and optimize business outcomes using AWS and Snowflake. · Development and management of interactive dashboards and reports in tools such as Power BI and Tableau to visualize key performance metrics. · Collaboration with stakeholders to understand business needs, translating them into analytical projects and actionable insights. · Management and optimization of cloud-based data architecture in Snowflake to ensure scalability and performance for analytics workloads. · Integration and analysis of large datasets to identify opportunities for business growth and operational efficiency. · Mentoring team members in advanced analytics techniques and best practices to foster innovation and data literacy within the organization.
Skills: Tableau (advanced dashboard design, visual storytelling) · Amazon QuickSight (interactive cloud visualizations) · Sisense (custom KPIs and dashboards) · Agile methodologies (Scrum, Kanban) · Talend (data integration and transformation) · Python (report automation) · Amazon Redshift (query optimization) · SQL (reporting queries) · Tableau Prep (data cleaning and preparation) · ETL tools (data flow automation) · Data Studio (dynamic reports) · Google Analytics (web metrics and behavioral reporting) Responsibilities: · Execute data extraction, cleansing, and processing operations ensuring data quality for effective visualization across multiple platforms. · Design, develop, and maintain automated reporting processes with a focus on clear and actionable visualizations for different audiences. · Implement data visualization best practices to effectively communicate insights through various tools such as Tableau, QuickSight, and Data Studio. · Create and maintain interactive dashboards that provide clear visibility of critical business KPIs, ensuring an intuitive user experience. · Conduct visual data analysis to identify trends and patterns, translating complex data into comprehensible stories for stakeholders. · Support data management projects focused on improving accessibility and visualization of key information for decision-making.
Skills: Data Studio (report visualization) · Power BI (interactive dashboards) · Google Analytics (web analytics) · Big Query (data processing) · Python (report automation) · SQL (data queries) · DV360 (programmatic advertising) · Facebook Ads (social campaign analytics) · Google Ads (search campaign analytics) · Supermetrics (advertising data integration) · Campaign Manager · Search Ads 360 · Amazon Ads Responsibilities: · Obtain valuable KPIs for digital and television media, performing customer segmentation, modeling, and tracking of advertising campaigns focused on cost reduction and target audience reach. · Develop and maintain cross-channel attribution models to evaluate the effectiveness of marketing campaigns across different touchpoints. · Design and implement A/B testing strategies to optimize campaign performance and creative effectiveness. · Create predictive models for media budget allocation and ROI forecasting across channels. · Build automated reporting systems for real-time campaign monitoring and optimization across platforms (DV360, Facebook Ads, Google Ads). · Analyze competitor advertising strategies and market trends to identify opportunities and optimize media spend. · Perform advanced audience analysis using first and third-party data to identify high-value segments and targeting opportunities. · Develop custom attribution models to understand the customer journey and optimize media mix allocation. · Generate weekly and monthly performance reports with actionable insights for clients and internal teams. · Collaborate with media planning teams to optimize campaign delivery and performance based on data insights.
Skills: SAS (statistical analysis and data mining) · SQL (data querying and manipulation) · MicroStrategy (data visualization and analysis) · Power BI (interactive dashboards) · Excel (data analysis and modeling) · Hadoop · Python (automation and analysis) · CRM tools Responsibilities: · Propose and execute relationship marketing strategies in accordance with the Commercial Activation Plan defined by Strategic Business Management, aiming to improve loyalty indicators by leveraging Big Data from the company's main businesses. · Develop and maintain customer segmentation models based on value, behavior, and lifecycle. · Design and implement personalized retention and loyalty campaigns using RFM (Recency, Frequency, Monetary) analysis. · Analyze customer behavior and purchase patterns to identify cross-selling and up-selling opportunities. · Create and optimize customer journey maps to enhance experience and increase retention. · Develop predictive models to identify customers at risk of churn. · Measure and analyze customer lifetime value (LTV) to optimize retention strategies. · Generate periodic reports on loyalty KPIs and loyalty program effectiveness. · Collaborate with marketing and sales teams to implement data-driven strategies.
Skills: R (statistical analysis and visualization) · Tableau (dashboard and report design) · SAS (data processing and analysis) · SQL · Excel (advanced analysis) · Power BI · Python Responsibilities: · Transform data provided for various requirements into valuable information for internal processes, allies, and partners through reports, dashboards, segmentations, and campaign outcomes. · Design and maintain interactive dashboards that facilitate data-driven decision making. · Perform customer and market segmentation analyses to identify business opportunities. · Develop automated reports to monitor key business KPIs. · Create effective visualizations that communicate complex insights in a clear and actionable manner. · Collaborate with internal and external teams to understand analysis needs and propose solutions. · Implement statistical analysis methodologies to evaluate campaign and program performance. · Maintain data quality and consistency in generated reports and analyses.