Salary
≈ $100k – $186k per year (Estimated)
Location
In office (London)
Seniority
Senior
Employment
Contractor
Confirmed on the employer's own hiring board on Oct 18, 2026. First seen by Alion on Jan 6, 2026. G MASS Consulting scores A on the Alion truth index.
Overview
Company
Impact
Profile match
Founded in 2023 as part of the Goodman Masson group, G MASS Consulting is a specialist resource augmentation and consulting firm headquartered in London, United Kingdom. The company specializes in delivering targeted technical expertise and skills-mapping solutions for the financial services industry. Utilizing its proprietary Talent Analytics Engine, G MASS provides specialized services spanning operational resilience, regulatory compliance remediation, digital asset product launches, cross-border expansion support, and enterprise change and transformation management.
G MASS Consulting are supporting a leading Audit and Advisory business. We’re looking for a Machine Learning Engineer to shape and scale their pricing technology. In this role, you’ll design and own ML platforms that streamline pricing workflows, support rapid model deployment, and ensure models perform reliably at scale. Partnering with Data Science, Actuarial, and Product teams.
Responsibilities:
- Build and support ML lifecycle tooling for model deployment, monitoring, and alerting
- Maintain and improve the Kubeflow environment for Data Scientists and Actuaries
- Create pricing analytics tools to accelerate impact analysis and reduce manual work
- Collaborate with pricing and product teams to deliver high-impact tooling
- Communicate complex concepts clearly to technical and non-technical audiences
Requirements
- Bachelor’s or Master’s degree in Statistics, Data Science, Computer Science, or a related field
- Strong experience managing the full ML model lifecycle (batch and online)
- Solid understanding of statistical methods, including GLMs and modern ML techniques
- Proven ability to build and deploy production-quality Python applications (pandas, scikit-learn)
- Experience with DevOps and ML tooling, including Kubernetes, Docker, CI/CD, and git-based workflows
- Familiarity with cloud platforms (AWS) and cloud data warehouses (Snowflake/SQL)
Benefits
Salary: to be discussed, depending on experience
Length: 12 months, with the view to extend
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