Analytics & AI Leader
Marcus Grant
Director of Analytics · Open Loot Studios
Wharton MBA · Palmer Scholar
Yale BA
Army Ranger · Bronze Star
AI & ML
Growth Analytics
Director of Analytics · Open Loot Studios
Marcus Grant is a Director of Analytics at Open Loot Studios, where he leads data-driven strategy across a portfolio of eight games generating over $170M in revenue. He specializes in applying AI, advanced analytics, and experimentation to drive user growth, monetization, and operational efficiency, working closely with C-suite leadership and engineering teams.
Prior to Open Loot, Marcus built machine learning and financial modeling solutions at Verizon and Mercor AI, focusing on optimizing large-scale business decisions. He holds an MBA from the Wharton School, where he was a Palmer Scholar (top 5%), and a BA from Yale University.
Before his business career, Marcus served as an Infantry Officer in the U.S. Army, earning a Bronze Star and ranking as the top junior officer in a special operations unit. He combines a background in leadership, analytics, and operations to drive high-impact business outcomes in complex environments.
Leads data-driven strategy across an 8-game portfolio generating $170M+ in revenue. Partners with C-suite and engineering on AI, experimentation, user acquisition, and monetization initiatives.
Applies machine learning and AI methodologies to optimize large-scale business decisions and platform operations.
Built ML and financial modeling solutions focused on optimizing large-scale business decisions across enterprise operations.
Led teams in a special operations unit, earning a Bronze Star and ranking as the top junior officer. Developed expertise in high-stakes decision-making, operations, and leadership under pressure.
End-to-end ML pipeline that segments players into behavioral clusters using 14 economic features, PCA dimensionality reduction, and K-Means. Runs on a rolling 30-day basis and tracks cluster migration over time via Sankey diagrams and transition matrices.
View on GitHub →Automated analytics agent that pulls daily KPIs from BigQuery, computes day-over-day and rolling period comparisons, and uses Gemini 2.5 Pro to generate a concise narrative summary — flagging anomalies and surfacing movers without human intervention.
View on GitHub →Multi-CTE SQL model tracking cost-per-token-issued across all issuance channels. Incorporates live price feeds and produces 7-, 30-, and 90-day rolling efficiency metrics for real-time economic health monitoring.
View on GitHub →NLP pipeline that scrapes 24-hour community messages, generates an abstractive summary via BART-large-cnn, and runs per-message sentiment classification to surface negative feedback themes for product and community teams.
View on GitHub →Two-part detection suite: statistical profiling of speed hack telemetry across 750k+ events, and percentile-threshold detection of reward grant abuse — with automated suspension duration recommendations exported for enforcement action.
View on GitHub →I work with companies looking to build or scale their analytics and AI capabilities. Whether you're trying to grow your user base, make sense of your data, or implement AI-driven solutions, I can help you move faster and make better decisions.
Analytics leadership, AI/ML, growth strategy, and military service — complete work history and credentials.