Quantitative hedge fund applying statistical ML to market prediction
The Voleon Group is a Berkeley-based quant hedge fund whose data stack (Spark, Flink, Iceberg, Trino, Dagster, Airflow, Polars) reads like a modern lakehouse built for research at scale. Hiring is accelerating and skews senior, led by engineering and research, with active work on data lineage, observability and migrating bespoke workflows onto shared platform abstractions.
Notable leadership hires: Business Operations Director
The Voleon Group is a privately held quantitative investment firm founded in 2007 and headquartered in Berkeley, California. The firm uses statistical machine learning to tackle large-scale financial prediction and portfolio construction problems. Its workforce sits in the 201–500 employee range and includes many researchers with doctoral training in quantitative fields. Teams span engineering, research, data, operations, finance and legal, with hiring in the United States and United Kingdom.
Voleon runs Python, C++ and Go with a data stack of Apache Spark, Flink, Iceberg, Trino, Presto, Parquet, Polars and Pandas, orchestrated by Airflow and Dagster on Kubernetes, monitored with Prometheus and Grafana.
Yes. Hiring is accelerating and led by engineering and research, with data roles close behind; most openings are senior-level, based in the United States and United Kingdom.
Current initiatives include productizing optimization for live trading, observability across the strategy lifecycle, platform migrations to shared abstractions, vendor data integration tooling, and data cataloging, versioning and lineage.
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The Voleon Group's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.