Resource augmentation and ML consulting for financial services
G MASS pairs recruitment-backed resource augmentation with consulting delivery across Financial Services and Insurance. The tech stack—Kubeflow, Kubernetes, Snowflake, Kafka, and a full ML ops toolchain—signals a shift beyond pure staffing toward building internal ML capabilities for clients. Active hiring across engineering, data, and ops (45 roles in 30 days) and projects like ML platforms for pricing and derivatives reporting suggest the firm is scaling its own data and engineering bench to match client transformation scope.
Notable leadership hires: KYC Onboarding Lead, Programme Director
G MASS is a specialist resource augmentation consultancy part of the Good Together Group, based in London. They serve mid-market and enterprise Financial Services and Insurance firms, combining recruitment capability with consulting delivery and governance. The business focuses on designing target operating models, implementing large derivatives platforms (Calypso), overhauling client onboarding workflows, and building ML infrastructure for pricing and portfolio management. Recent project activity includes EMIR 3.0 regulatory reporting, private debt lifecycle management, and asset servicing process redesign. They hire across the UK and US.
Python, Kubernetes, Docker, Snowflake, Kafka, Salesforce, AWS (Lambda, ECS, RDS), PostgreSQL, MongoDB, Jenkins, React, and TypeScript. They're adopting Gemini and run ML infrastructure using Kubeflow and scikit-learn.
London, UK. They hire in both the United Kingdom and United States, with hiring velocity accelerating.
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G MASS Consulting'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.