At a Glance
- Tasks: Lead the finance product experience and automate robotics financing processes.
- Company: Cenotian, a pioneering fintech in robotics asset securitisation.
- Benefits: Competitive salary, impactful role, and rapid growth opportunities.
- Other info: Join a fast-paced environment with significant influence and innovation.
- Why this job: Shape the future of asset-backed robotics financing in a dynamic market.
- Qualifications: 5-7 years in investment roles with strong quantitative skills.
The predicted salary is between 70000 - 90000 £ per year.
Cenotian is an early‑stage, Tier‑1 backed fintech securitizing industrial robotics and automation assets into a new, prime fixed‑income asset class. Combining institutional‑grade capital with specialized deployment infrastructure, Cenotian enables OEMs to scale globally without balance‑sheet exposure while providing investors access to a novel, high‑quality asset category.
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‑sloped role for a builder‑investor bridging finance and engineering.
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.
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.
The ideal candidate
- 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.
