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Algorithm Engineer
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 algorithm engineers to join our Algorithm Engineering 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. 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 new features for Ki's underwriting algorithm for risk assessment and portfolio management 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 Ensure the Ki algorithm is always online and available to generate line sizes Design and implement enabling services that makes the Ki algorithm more efficient, flexible and scalable Exercise software engineering best practice to ensure our algorithm product is built in line with Ki's broader engineering standards Support the integration of the Ki algorithm into the other core components of the broader platform Guide junior members to help them improve their engineering skills and understanding of the insurance market
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.
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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.
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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.
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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.
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Understanding of Machine Learning approaches and algorithms Understanding of the control and management of data products and machine learning algorithms Experience with python programming and various software design patterns Direct experience with at least one cloud provider required Experience working in regulated industry, especially financial services and insurance would be a plus Commercially minded, knowledge of the insurance market would be ideal or an aptitude/interest to learn more about the industry and how it operates Experience using project management and workflow tools (e.g. Jira) Experience with CI/CD tools such as GitHub Actions, Circle CI, Jenkins
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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