Marketing mix modeling software with automated scenario planning
MASS Analytics builds marketing mix modeling software—a Python + R + Snowflake + Databricks stack designed to automate budget optimization and ROI measurement. Active projects reveal a focus on scaling model reliability (multicollinearity mitigation, schema-resilient ingestion) and speed (automated scenario simulation), while pain points around slow scenario construction and manual intervention suggest the product still requires optimization in operational efficiency. Hiring has decelerated to one role in the past month, concentrated in intern-level data and engineering positions.
MASS Analytics is a UK-based marketing analytics software company founded in 2015, operating out of Hammersmith, England. The product delivers marketing mix modeling—a quantitative approach to understanding conversion drivers and optimizing media spend allocation. The platform uses Python, R, Apache NiFi, Iceberg, Snowflake, and Databricks to construct automated, machine-learning-driven models. The company serves mid-market and enterprise clients across marketing departments and agencies. Current operational priorities include regional expansion into the UAE and MENA, alongside infrastructure hardening to reduce schema-related downtime and improve scenario simulation speed.
MASS Analytics runs Python, R, Apache NiFi, Snowflake, Databricks, and Iceberg as core components, with AWS and Azure for cloud infrastructure, Docker for containerization, and Jira + Confluence for internal tooling.
MASS Analytics has 7 active roles with 1 posted in the past 30 days. Hiring is concentrated in intern-level positions (5 open) across engineering, marketing, data, and sales, with recruitment currently limited to Tunisia.
Priority projects include multicollinearity mitigation in marketing mix models, automated scenario simulation pipelines, schema-resilient data ingestion, and an always-on analytics application for the Databricks Marketplace, alongside UAE/MENA regional expansion.
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