Algorithm Engineer

Algorithm Engineer

Full-Time 60000 - 80000 £ / year (est.) Hybrid
K

At a Glance

  • Tasks: Design and develop cutting-edge algorithms for risk assessment in insurance.
  • Company: Join Ki, the fastest growing algorithmic insurance carrier in the world.
  • Benefits: Competitive salary, remote work options, and opportunities for professional growth.
  • Other info: Dynamic, multi-disciplined team focused on innovation and impactful projects.
  • Why this job: Be part of a revolutionary team transforming the insurance industry with technology.
  • Qualifications: Experience in machine learning, Python programming, and cloud services required.

The predicted salary is between 60000 - 80000 £ per year.

Who are we? 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 and the fastest growing syndicate in the Lloyd's of London market, being 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 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:

  • 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 make 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.

Qualifications:

  • 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.

Algorithm Engineer employer: Ki Insurance

Ki is an exceptional employer, offering a dynamic and innovative work environment at the forefront of the insurance industry. With a strong focus on employee growth, Ki provides opportunities for professional development and encourages collaboration across diverse teams. Located in the heart of London, employees benefit from a competitive remuneration package and a culture that values recognition and rewards outstanding contributions.

K

Contact Details:

Ki Insurance Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Algorithm Engineer

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✨Apply Directly through Our Website

When you find a suitable opening like Algorithm Engineer at Ki Insurance, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!

We think you need these skills to ace Algorithm Engineer

Machine Learning
Python Programming
Software Design Patterns
Cloud Computing
Data Management
Algorithm Development
Risk Assessment

Some tips for your application 🫡

Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!

Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!

Craft a Tailored Cover Letter:For a full-time role at Ki Insurance, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.

Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Ki Insurance. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!

How to prepare for a job interview at Ki Insurance

✨Brush Up on Your Statistics

For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!

✨Showcase Your Projects

Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!

✨Get Comfortable with Python and R

Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Ki Insurance!

✨Prepare for Case Studies

Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.