Case Study: MScience achieves scalable, ML-powered insights and 21 new data products with Databricks

MScience - Customer Case Study

MScience helps top financial institutions turn traditional and alternative data into predictive investment insights. As data volumes exploded, their on‑prem PostgreSQL setup and fragmented toolchain slowed processing, forced analysts to store work locally, and limited teams to SQL/Excel—creating delays, poor collaboration, and constrained analytics.

By moving to Databricks’ serverless cloud platform with shared interactive workspaces and MLflow, MScience automated infrastructure, unified teams, and streamlined the ML lifecycle. The platform enabled 21 new data products, scalable pipelines handling 5–10 million records per day, removed operational complexity, and accelerated cross‑team collaboration and experimentation.

MScience

Ajay Krishna

Head of Data Science and Engineering