AI-powered out-of-home advertising with geolocation data and campaign measurement
Billups operates a data-intensive OOH advertising platform built on PySpark, Databricks, and Redshift, handling terabyte-scale geolocation pipelines and campaign attribution models. The tech stack and active projects reveal a company in transition: moving from legacy systems toward modern data infrastructure (Airflow, Prefect, Dagster orchestration), while actively productionizing ML models for campaign analysis and measurement—the industry's hardest technical problems. Sales hiring (9 open roles) outpaces engineering (2), signaling customer acquisition focus over platform expansion.
Notable leadership hires: Business Director
Billups is a performance-driven out-of-home advertising platform serving mid-market and enterprise brands. Founded in 2003 and headquartered in New York, the company operates across 20+ countries with a 450+ person team. The core product combines programmatic ad placement, geolocation targeting, and campaign measurement for physical media (DOOH and pDOOH). Revenue model relies on media planning, media buying, and managed services. Current technical priorities include automating data pipelines at scale, improving OOH campaign attribution, and modernizing legacy infrastructure—pain points endemic to media tech companies managing high-volume, real-world measurement data.
PySpark, Databricks, Python, Apache Spark, Redshift, ClickHouse, Airflow, Prefect, Dagster, PostGIS, GeoPandas, AWS (SQS, SNS), Kubernetes, Terraform, React, .NET, GitHub Actions.
Rebuilding PySpark/Databricks pipelines for geolocation data, automating core data prep, productionizing campaign analysis models, improving OOH measurement and attribution, and modernizing legacy systems.
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