Experimentation & Causal Inference
A/B testing, multivariate testing, power analysis, treatment/control design, uplift and statistical decision criteria.
APPLIED STATISTICS FOR DECISION-MAKING
Vanessa Martins Pinto
Experiments, causal inference and quantitative analysis to measure impact with rigor.
I turn business questions into testable hypotheses, define metrics and comparison groups, validate assumptions and communicate results with uncertainty, limitations and predefined criteria.
Target roles: Experimentation Analyst · Statistical Analyst · Data Scientist - Experimentation · Quantitative Research Analyst · Causal Inference Analyst
Selected Cases
Statistical methods applied to measurable questions, explicit assumptions and decision criteria.
Experiment Design and Causal Impact Measurement
Design and analysis of controlled experiments to estimate incremental impact and support decisions grounded in evidence.
Time Series Impact Analysis and Counterfactual Forecasting
Evaluation of whether an observed change in a metric was caused by an intervention or by trend, seasonality, or noise.
Quantitative Portfolio and Pricing Optimization
Simulation-based approach to optimize offer mix, pricing scenarios, attribute value and expected market share.
Applied Methods
A focused portfolio across experimentation, statistical modeling, quantitative intelligence and text-based automation.
Statistical Modeling
Time series inference, survival analysis, forecasting, hypothesis testing and uncertainty estimation.
Quantitative Intelligence
Market sizing, pricing, portfolio optimization, segmentation, churn, LTV and ROI analysis.
NLP & AI Automation
Text analytics, entity extraction, summarization, RAG systems and knowledge-base automation.