Samuel Merikallio

I like finding the story inside the data and figuring out what it means for the next decision.

My background sits at the intersection of media, marketing, analytics, and audience behavior. Over the years, I’ve worked across paid media, user acquisition, campaign performance, forecasting, experimentation, budget allocation, and reporting, while becoming increasingly focused on how data can explain what audiences watch, why certain content performs, and where trends are heading.

What I enjoy most is going deeper than the surface-level numbers. I like building dashboards, testing hypotheses, finding patterns, and connecting performance data to a broader business or audience story. More recently, I’ve expanded my work into entertainment analytics through independent projects focused on streaming performance, genre trends, content economics, and viewer behavior, while developing stronger capabilities in SQL and Python.

Throughout my career, I’ve supported marketing, media, analytics, and cross-functional teams managing large budgets, complex datasets, multi-channel campaigns, and reporting systems. I’ve worked across paid social, search, programmatic, CTV, app acquisition, data visualization, statistical analysis, and marketing mix modeling, with a consistent focus on helping teams understand what is working, what is not, and what the data suggests they should do next.

◆ Portfolio: https://cerulean-chimera-8fd9ac.netlify.app/
◆ Substack: wimpyboysocialclub.substack.com
◆ Youtube: https://www.youtube.com/@WimpyBoySocialClub

Expertise
🔹 Content Performance Analysis
🔹 Audience & Consumer Insights
🔹 Streaming & Media Analytics
🔹 Growth & Marketing Analytics
🔹 Data Storytelling
🔹 Forecasting & Scenario Analysis
🔹 Dashboard Development & Visualization
🔹 Statistical Analysis & Experimentation
🔹 Media Mix & Performance Analysis
🔹 SQL, Python & BI Tools

Career Highlights

◆ Managed performance analysis across $20M in monthly Meta and Google media spend supporting major products and markets.

◆ Identified $300K in annual media waste through structured experimentation and ANOVA analysis, helping redirect spend toward stronger-performing channels and campaigns.

◆ Built automated reporting and analytics systems that eliminated 15 hours of manual reporting work each week and combined data from 15+ sources.

◆ Researched 60 years of television programming and built an original dataset that became the analytical foundation of a 3-hour documentary that reached 40,000+ viewers.