Responsibilities & achievements

As a Data Scientist at Mercado Libre, you will play a pivotal role in transforming raw data into actionable insights. Collaborate with cross-functional teams to uncover patterns, trends, and opportunities within the vast ecosystem of Latin America's leading e-commerce platform. Your expertise will drive innovation, enhance customer experiences, and fuel business growth.

Responsibilities & achievements

Statistical Modeling: Apply advanced statistical techniques to analyze financial data, providing actionable insights that aid decision-making. Machine Learning Algorithms: Develop and implement ML algorithms following CRISP-DM methodology, addressing challenges like customer loyalty and transaction-based segmentation. Data Preparation: Collect, clean, and preprocess data for modeling, ensuring its accuracy and relevance. Customer Loyalty Analysis: Explore and interpret customer behavior patterns to enhance loyalty strategies and retention efforts. Segmentation Strategies: Utilize transaction data to create meaningful customer segments, enabling targeted marketing and personalized services. Collaboration: Work closely with cross-functional teams to understand business needs and translate them into effective data-driven solutions. Model Evaluation: Assess model performance and iterate to improve accuracy and effectiveness. Documentation: Document methodologies, data sources, and results for clear communication and future reference. Stakeholder Communication: Present findings and recommendations to stakeholders, facilitating informed choices in financial strategy.

Responsibilities & achievements

Project Engagement: Contribute to diverse projects across sectors, engaging in the complete lifecycle of analytical initiatives. Machine Learning Expertise: Provide expertise in developing Machine Learning and Deep Learning models to drive informed business decisions. Early Project Stage: Engage from project inception, collaborating with teams to define objectives and establish data requirements. Analytical Dashboards: Design and construct analytical dashboards that showcase results obtained through descriptive, inferential, predictive, and cognitive statistics. Business Insights: Extract valuable insights from analytical findings, translating them into actionable recommendations for business strategy enhancement.

Responsibilities & achievements

Algorithm Development: Create and enhance hard rule algorithms, predictive models using Machine Learning, Deep Learning, and classical statistical approaches. Cross-Sector Solutions: Provide tailored solutions across various sectors (finance, health, technology) by adapting algorithms to meet unique challenges.