Data Analyst & Analytics Consultant
Marketing, Revenue & Growth Analytics
New York, New York
Victor Cornejo — Data Analyst & Analytics Consultant, New York City
I’m a New York–based data analyst and analytics consultant helping teams make better business decisions through data.
My work sits at the intersection of analytics, strategy, and marketing, supporting clients across SaaS, real estate, hospitality, and professional services. I partner with teams to turn messy, real-world data into clear insights that support growth, operational efficiency, and smarter decision-making.
I lead projects end-to-end — from organizing and analyzing raw data across POS systems, marketing platforms, and customer data sources to building dashboards, identifying performance trends, and translating findings into actionable recommendations for stakeholders and leadership teams.
My core tools are Python, SQL, and Tableau, but my focus is always on the business problem first. I’ve worked on projects involving marketing performance, pricing strategy, customer behavior, demand forecasting, and media mix analysis, helping clients better understand what’s actually driving results.
Before transitioning fully into analytics, I trained in law — a background that shaped how I approach problem-solving: structured thinking, attention to detail, and a strong bias toward evidence-based decision-making. Combined with client-facing experience, it allows me to communicate complex analysis clearly to both technical and non-technical audiences.
Fluent in English and Spanish, I’m comfortable working cross-functionally and supporting conversations with leadership teams, helping organizations move from raw data to confident business decisions.
Selected Analytics Work
A selection of client-style analytics projects focused on growth, retention, and real-world marketing performance.
Key Drivers of Churn — Translating Model Coefficients into Actionable Insights
Model Performance — Comparing models to identify the strongest classifier for targeted churn-reduction
Channel impact on revenue — identifying where marketing spend drives the most value
Experiment design — testing causal impact before scaling budget decisions
Marketing performance by spend tier — identifying where investment begins to drive incremental revenue
Recommended budget strategy — focusing investment where marketing drives measurable impact