Felipe S

Sr. Data Analyst | RD Saude

Health.gov • Tiempo completo

Jan 2026 - Present • 8 mos

• Designed and executed A/B tests to optimize the healthcare services scheduling funnel (vaccines, exams, weight loss programs): formulated hypotheses, defined primary and guardrail metrics, calculated sample sizes, and monitored statistical significance throughout experiments. • Identified friction points across the funnel and led causal analysis on drop-off factors, translating insights into recommendations adopted by the product team. • Built a predictive scheduling model (Scikit-learn) to forecast demand by region and time period, supporting capacity planning decisions. • Developed and maintained dashboards to track healthcare KPIs (conversion, retention, service NPS), serving as an analytical partner for both technical and business stakeholders. • Managed health data ETL pipelines (SQL, BigQuery, Amazon Redshift), ensuring metric integrity and traceability.

Sr. Data Analyst | Braze

Brazos Bounce • Tiempo completo

Jan 2025 - Jan 2026 • 1 yr

• Addressed analytical demands from global internal teams, extracting and analyzing data via SQL and LookML to support decisions regarding product adoption and user engagement. • Led the standardization of dashboards: migrated individual ad-hoc reports into company-wide consolidated dashboards, increasing consistency and reducing analytical rework across teams. • Worked directly with international stakeholders, gathering requirements, communicating findings, and ensuring the quality and integrity of reported data.

Sr. Business Analyst | Nubank

Banks • Tiempo completo

Jul 2021 - Feb 2024 • 2 yrs 7 mos

• Responsible for the design, execution, and monitoring of A/B tests for the communication pipeline (email, push, in-app): defined control and treatment groups, success metrics, and stopping criteria, ensuring the statistical validity of experiments. • Conducted segmentation and cohort selection analysis for a financial product migration: identified customer profiles with higher value propensity, validated hypotheses through a controlled experiment, and presented results to the product team — leading to policy adoption. • Optimized a customer income and spending forecasting model by incorporating internal and external variables (Spark Scala, Python) — model utilized for risk segmentation and personalized offers. • Performed performance, trend, and benchmark analyses using Spark Scala and SQL in Databricks and BigQuery, delivering regular presentations to technical stakeholders and business leaders.