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As a versatile data professional at Familify, I support the entire company by fulfilling various roles including Data Analyst, Data Engineer, and Data Scientist. My primary focus is on Growth, especially for our subscription-based app where most users are paid subscribers. Key Contributions: Control Dashboards Development: Created multiple dashboards for various departments, particularly for Growth Acquisition, to monitor key metrics like investment, costs, and ROI, enabling informed decision-making. Forecasting Model: Developed a forecasting model in Google Sheets to analyze trends and predict future performance, aiding in strategic planning for upcoming days. Data Engineering: Enhanced data models and schemas on Google BigQuery using low-code ETL tools like Fivetran, and developed pipelines with Google Cloud Functions and Google Cloud Storage. Event Data Quality: Improved event data quality by analyzing and ensuring the accuracy of data fields, collaborating closely with the Product/Tech team. Strategic Data Analysis: Provide critical data analysis and insights to the CEO, supporting key strategic decisions across the company.

As a key member of Papumba's Data Team, I was instrumental in developing and refining the company's data infrastructure. My efforts focused on building foundational data models that drive crucial business insights and enhance strategic decision-making. Key Contributions: Google BigQuery Data Models: Led the development of core data models, emphasizing event data and integrating ad network data via Fivetran, which served as the backbone for advanced analytics. Company Dashboard in Looker Studio: Played a central role in launching a comprehensive dashboard in Looker Studio, enabling the company to track and analyze vital business metrics, thereby improving decision-making processes. Customer Lifetime Value (LTV) Model: Worked under my manager's guidance to create a model for calculating customer lifetime value, factoring in initial purchases and renewal rates. This model has become a critical tool for understanding customer retention and driving strategic planning. Retention Analysis Using Python: Applied advanced data science techniques, such as conditional likelihood, to analyze retention patterns. This analysis provided deep insights into customer behavior, allowing for more effective engagement strategies and improved retention. These accomplishments at Papumba highlight my ability to leverage data for impactful analysis, ultimately boosting both strategic foresight and operational efficiency.

In my role as a Business Analyst at PedidosYa, I played a key part in supporting and enhancing the Customer Service Team's operations. At the time of my joining, the team lacked dedicated data tools, so my initial focus was on understanding their needs and how data could be leveraged to improve their processes. Key Contributions: Collaboration for Data Integration: Worked closely with the Data Customer Care Team to understand existing data models and tools, and collaborated with the Customer Service Team to define key metrics and establish methodologies for measuring operational efficiency. Development of Automated Control Dashboards: Spearheaded the creation of comprehensive, automated control dashboards. These dashboards significantly reduced manual workloads, allowing the team to focus on critical tasks and enhancing overall operational efficiency. Support for Outsourcing Teams: Provided essential data reporting tools to various outsourcing teams, enabling them to effectively measure and improve the performance of their customer service operations.

I began my career as an intern, where alongside the intern team, we developed tools designed to automate tasks for other teams, saving them significant time. My primary focus was on Python for automation and conducting visualization projects using Power BI. After four months, I was promoted to a full-time position as a Business Analyst within the IT Sales & Post Sales Team. In this role, I was responsible for understanding and identifying business requirements and opportunities for improvement. I also mapped out new features for SAP Systems, acting as a liaison between the business units and SAP developers. My responsibilities included ensuring that new features were developed correctly and delivered on time, facilitating smooth operations and contributing to the overall efficiency of our processes.