You will own the end-to-end finance product experience, transforming underwriting judgment into scalable machinery for robotics financing. You’ll build Cenotian’s core data ontology and risk model stack, utilizing SQL and Python to turn deal intake into auditable, automated outcomes. This is a high-slope role for a builder-investor bridging finance and engineering.
VP, Data & Underwriting at Cenotian
Cenotian is pioneering the world's first asset-backed financing platform for robotics and industrial automation, and they are seeking a VP of Data & Underwriting to own the entire finance product experience. This is not a typical credit seat; you will be a technically sharp finance generalist building the automated machinery and data ontology that secures institutional trust. If you are a high-slope builder with investment rigor and coding leverage, this is your opportunity to architect a new, prime fixed-income asset class from the ground up.
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Location
London, United Kingdom
Compensation
Not Disclosed
Company
Cenotian
Role overview
Cenotian provides deployment capabilities and capital for industrial and commercial automation. The company focuses on enabling robotics and automation OEMs to scale equipment sales through asset-backed financing structures. Its model is inspired by aircraft leasing but designed to remove operational burden from OEMs, allowing them to offer their customers flexible, finance-enabled deployments of robots and automation equipment. Cenotian’s platform securitizes financed equipment into pooled structures to create a fixed-income product backed by robotics and automation assets, unlocking lower-cost capital for end customers and investors while facilitating broader adoption of automation technologies in industrial and commercial settings.
What you will do
- Own the entire deal lifecycle from intake to contracting, industrializing judgment into an exception-driven, automated finance-grade product experience.
- Build and maintain the compounding data ontology and core risk model stack, including ontological warehouses and machine-readable contract primitives.
- Directly prototype decision-support systems and automation tools using Python and AI to remove manual work while maintaining investor-grade auditability.
Who this is a fit for
- Possesses 5-7 years of experience in high-velocity investment roles, management consulting, or structured finance with a strong quantitative STEM foundation.
- Demonstrates technical leverage, capable of querying data directly, shipping code for internal tools, and reasoning about complex data systems.
- Displays founder-grade ownership and an operator mentality, with the ability to translate ambiguous financial problems into crisp, repeatable execution machinery.
Why this role is remarkable
- Shape the intellectual framework and risk identity of a category-defining platform for the world's first asset-backed robotics financing.
- Scale rapidly with Tier-1 institutional equity and debt backing in an explosive market comparable to the early days of data centers.
- Enjoy outsized influence at an inflection point, building proprietary data moats that surpass traditional institutional architecture without operational burden.
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