Make analysis reusable. Package approved analyses into reproducible notebooks, parameterized pipelines or services with engineering support. Monitor data and model changes, explain results to advisors, and connect scenarios to Advisory/Simulation outputs.
A strong quantitative research or consulting record; typically 3+ years, with equivalent achievement considered. Practical statistics, data preparation and model validation.
Ability to demonstrate Python or R and SQL on a reproducible analysis, plus basic AI/ML learning and hands-on experimentation. A quantitative degree or equivalent applied capability is required....
Demonstrated client discovery, framework design, quantitative interpretation and cross-functional leadership. Foundational AI learning through a certificate, assessed course or equivalent, plus a practical example of AI-assisted research with source checking.
Preferred: Product management, solution design, workflow automation, industry knowledge modelling, business analytics or enterprise-platform exposure. An MBA or relevant postgraduate qualification is useful, not mandatory.
Entry level and authority: Business-led entry does not require production coding. Appointment as Lead Architect - Technology requires separate evidence of software architecture, integrations, secure deployment and technical delivery; an AI certificate alone is insufficient....
Connect business and technology. Partner with technical trainers on experiment design and failure diagnosis. In the technology variant, additionally build Python evaluation scripts, manage dataset versions and support approved fine-tuning experiments where justified.
Substantial hands-on research, consulting or knowledge-quality experience; typically 3+ years, with equivalent achievement considered.
Strong evidence assessment, business writing, numerical checking and attention to methodological detail....
Operationalize the analysis: Create reproducible code, data tests and documented model interfaces. Build scenario outputs, drift/quality monitoring and visual explanations; integrate approved models with MetaBrain workflows through engineering review.