Open to opportunities

José Estevan

@josestevan

I turn product and growth data into experiments, models, and decisions that improve revenue, retention, and acquisition.

Brazil

Message

What I'm looking for

I'm looking to turn ambiguous product, growth, and operational questions into experiments, models, and reliable data products that drive measurable adoption, retention, revenue, and acquisition outcomes.

I've led product and growth analytics at iFood, where my work saved $1.3M per month, reduced CAC by 15%, and increased M+1 retention by 24%.

I build decision-ready data products end to end: from framing ambiguous questions and designing experiments to rebuilding unreliable event pipelines, deploying propensity models, and enabling self-service analytics. Across iFood, I improved conversion by 23%, scaled experimentation to 30+ tests per month, and reduced recurring analytics requests by 60%.

Through Artha Analytics, I help teams redesign activation and lifecycle strategies using tested dbt models, product behavior, and Habit Moment targeting. This work helped reduce churn from 35% to 14% and increase monthly-to-annual expansion from 5% to 17%.

Experience

Work history, roles, and key accomplishments

Current

Senior Data Analyst

Current

Artha Analytics

Oct 2025 - Present (10 months)

Led product and growth analytics practice, redesigning activation around Setup, Aha, and Habit milestones, and building dbt lifecycle models that increased monthly-to-annual expansion from 5% to 17%.

Product Analytics Growth Analytics DBT Lifecycle Experimentation

Senior Data Analyst

iFood

May 2024 - Mar 2025 (10 months)

Led acquisition experiments saving $1.3M/month and reducing CAC by 15%, prevented feature retirement by rebuilding event data in PySpark, increased M+1 retention by 24%, and built self-service Tableau layers reducing analytics requests by 60%.

SQL Python PySpark DBT Tableau Experimentation Decision Trees Data Modeling

Data Analyst

iFood

Dec 2022 - May 2024 (1 year 5 months)

Operationalized a CatBoost propensity model generating $190K/month incremental revenue and lifting conversion 23%, built Python spend-velocity monitoring preventing overspend, and scaled experimentation to 30+ tests/month.

SQL Python CatBoost Experimentation Slack

Data Analytics Intern

iFood

Mar 2021 - Dec 2022 (1 year 9 months)

Developed Python time-series models reducing forecast error by 14% and automated Tableau dashboards that shortened stakeholder analysis time by 42% and increased data-product adoption by 37%.

Python Time Series Analysis Tableau Dashboarding Documentation Training