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Who are we?π
Look at the latest headlines and you will see something Ki insures. Think space shuttles, world tours, wind farms, and even footballers' legs.
Ki's mission is simple. Digitally disrupt and revolutionise a 335-year-old market. Working with Google and UCL, Ki has created a platform that uses algorithms, machine learning and large language models to give insurance brokers quotes in seconds, rather than days.
Ki is proudly the biggest global algorithmic insurance carrier. It is the fastest growing syndicate in the Lloyd's of London market, and the first ever to make $100m in profit in 3 years.
Ki's teams have varied backgrounds and work together in an agile, cross-functional way to build the very best experience for its customers. Ki has big ambitions but needs more excellent minds to challenge the status-quo and help it reach new horizons.
Where you come in?
We're looking for a Senior Algorithm Engineer to join our Algorithmic Underwriting team. You will work at the intersection of underwriting and algorithm development, developing machine learning-enabled products that operate across over 25 classes of business ranging from Commercial Properties to Oil Rigs to Event Contingency insurance.
You will help us better evaluate every single risk on its own merits, and on how it helps us build a profitable and stable portfolio, all in the space of under a minute. From large scale geospatial analysis to manage our exposure to natural catastrophes to research and development on low data volume machine learning approaches for classes of business with very few claims (like Terrorism insurance!). We operate at the point where the two very different worlds of technology and specialty insurance meet, and you will be part of both.
Reasons to use Rodeo
Iβm in my final year doing Economics and I donβt know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer β it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) donβt need a masters. Letβs look at the ones youβd be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet β that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant β 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
See breakdownIt searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
Youβve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon β deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme β client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right β and where to focus when applying.
We're a multi-disciplined team and pride ourselves on being commercially focused, bringing together deep expertise in specialty insurance and scalable machine learning product development. Our squads focus on delivering high-impact features and we favour a highly iterative, analytical approach. We invest time in research and development, internally and with academic institutions.
We focus on the commercial outcomes that our algorithm achieves, and we like (who doesn't?) well tested and maintainable code. Our algorithm is built in Python and our infrastructure is entirely cloud native and we maintain our infrastructure as code.
What you will be doing: ποΈ
- Design, develop and maintain algorithm related systems to carry out underwriting and portfolio management activities at scale
- Improve the robustness of the Ki algorithm by digitising the governance and control of our underwriting, actuarial and software processes, reducing our time to live
- Design and implement enabling services that makes the Ki algorithm more efficient, flexible and scalable
- Liaise with business stakeholder and product owner to build best algorithm product for customers
- Act as a knowledge hub with deep understanding of relevant Ki's business and tech stack
- Managing and developing junior members of the team
- Drive improvements in the way we operate as a digital underwriting capability


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Requirements
- Commercially aware, with a knowledge of the insurance market
- Understanding of the control and management of data products and machine learning algorithms
- Skilled using Python
- Experience using project management and workflow tools (e.g. Jira)
- Experience with CI/CD tools such as GitHub Actions, Circle CI, Jenkins
- Understanding of market compliance and core regulatory requirements
- Understanding of core insurance portfolio management principles and dynamics
- Experience developing industrialised machine learning applications and services
βIt took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what Iβve been looking for.β
Jessica, London
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