Pedro Alonso Email & Phone Number

Rio De Janeiro, Brazil

Chicago, Illinois, Estados Unidos

As the sole Data Scientist at eSpark Learning, I lead several data initiatives within the fast-paced EdTech space, powering data-driven improvements that enhance both product performance and educational outcomes. My responsibilities span the entire data lifecycle, with a focus on leveraging advanced AI techniques to transform how students and educators interact with technology.Data Pipeline Optimization: Engineered and streamlined data workflows, centralizing processes from data wrangling and feature engineering to model development, achieving increased pipeline reliability and supporting scalable insights across multiple teams.End-to-End Analytics Ownership: Led all analytical phases, from exploratory data analysis to model training and business reporting, ensuring actionable insights for stakeholders. Consistently provided data-backed strategies that drove improvements in product features, student engagement, and learning outcomes.AI/LLM Integration for EdTech Products: On GenAI, I handled the integration and continuous fine-tuning of the LLM-powered assistant within our flagship EdTech product, significantly enhancing the student and teacher experience through more interactive, personalized and accurate feedback.Business Intelligence for Strategic Growth: Built and optimized data validation, discovery, and testing frameworks, accelerating decision-making processes across product, engineering, and leadership teams. Introduced data-driven approaches that enabled faster time-to-market for new features and improved product-market fit.

Data Scientist/Analyst in the health care/tech field. Among my main responsibilities, I created the data science handbook for standardizing our AB tests, developing the protocols we use from experiment design (pre-test: minimum effect, confidence, power, runtime, success metric(s)...) to monitoring and processing. Strong emphasis on best practices in the statistical framework and inference.More specifically, in the realm of Machine Learning, I developed the churn model for the company's flagship product and conducted support studies using clustering and time series tools. I routinely use SQL, Python, and R, and I'm familiar with solutions within the AWS stack, such as SageMaker, Redshift, and EC2.Also heped build machine learning models for clustering and classification, derived insighs to solve segmentation, churning, pricing and product launching problems. Frameworks/Stacks of daily usage include Python, SQL and Excel.Focus on advanced analytics to help company decisions become more data driven.

Rio De Janeiro, Brasil

Data Scientist in a consulting project with a major TELCO player. Working on the modernization and structuring of the Artificial Intelligence and Machine Learning department. Participation in two major machine learning projects: Customer base clustering (approximately 15 million unique users); and Fiber optic product acquisition propensity (classification). Regular use of R/SQL/Python, reporting directly to senior leadership.

Mestrado, Statistics

Bacharelado, Business/Commerce, General