Analytics and BI | Revenue, retention, and fraud prevention
I turn product and customer data into measurable revenue, retention, and fraud-prevention wins.
Analytics professional with 5+ years across StackAdapt and BrokerLink, building BI, experimentation, and data systems that improve revenue, reduce fraud, and speed up decision-making.
150%
YoY CTV revenue growth
StackAdapt media encoding launch
70%
Faster fraud investigations
dbt models and Tableau monitoring
25%
Better revenue-to-impression ratio
Experiment design and backend optimization
40%
Commercial retention lift
Python and XGBoost targeting
How I help
Three ways I add leverage
Revenue analytics that drives action
I build KPI frameworks, stakeholder dashboards, and opportunity models that move from reporting to decision-making.
Experimentation with clean business signals
I scope ambiguous problems, define success metrics, and run measurement that helps teams ship changes with confidence.
Data systems that stay reliable under scale
I design pipelines, warehouse models, and quality checks that make analytics trusted, fast, and production-ready.
Selected wins
Proof that connects analytics work to business outcomes
150% YoY growth
CTV monetization for enterprise media demand
Led analytics support for a new media encoding pipeline that unlocked revenue from partners such as Disney, NBCU, and Paramount.
Under 3% fraud rate
Fraud monitoring that shortened investigations by 70%
Built data models and executive dashboards that surfaced anomalies in real time and cut manual investigation turnaround dramatically.
25% efficiency gain
Experimentation for platform and algorithm decisions
Designed A/B testing frameworks, success metrics, and evaluation logic that improved the platform-wide revenue-to-impression ratio.
40% retention lift
Churn targeting for commercial insurance accounts
Applied predictive modeling to identify cancellation risk and help stakeholder teams re-market the right accounts at the right time.
Featured work
Two places to go deeper
Project proof
Retail Customer Churn Prediction and Retention Analytics
An end-to-end churn system with warehouse modeling, ELT, explainable ML, and a Streamlit dashboard tied to projected revenue savings.
Work impact
Platform analytics across revenue, fraud, and experimentation
Highlights from StackAdapt and BrokerLink covering CTV revenue growth, fraud reduction, BI delivery, and retention modeling in production settings.
Core stack