At a Glance
- Tasks: Join the Algorithmic Underwriting team to build and optimise risk modelling algorithms.
- Company: Ki, a pioneering global algorithmic insurance carrier with a mission to disrupt the industry.
- Benefits: Competitive salary, flexible working, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on career development and cutting-edge technology.
- Why this job: Be part of a fast-growing company making waves in the insurance market with innovative tech.
- Qualifications: Experience in data science, machine learning, and Python; STEM degree 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. 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? Working within the Algorithmic Underwriting team, the Data Scientist focuses on the build, deployment, and safe operation of Ki's suite of risk modelling and risk selection algorithms. They collaborate with product, engineering, actuarial, and underwriting teams to develop models, experiment with new datasets and features, and integrate these into underwriting and portfolio management capabilities.
What you will be doing:
- Work with other data scientists, actuaries, engineers, and commercial teams to deliver and maintain production‑grade machine learning models at scale.
- Carry out regular monitoring, assessments, and optimisation of live data, models, and the underwriting algorithm to identify opportunities for improvement.
- Explore new ideas and emerging statistical, agentic and LLM, and machine learning approaches and technologies to understand how they can be embedded into the Ki algorithm or wider business processes.
- Drive improvements in the way we operate as a digital underwriting capability.
- Manage and/or support the development of junior members of the team.
Hands‑on Data Science experience (or a related role) within financial, fintech, or otherwise financial risk and predictive modelling context. Comfortable working in Python for production environments, experience with common software development and machine learning frameworks (e.g. GitHub, Copilot, Claude, CI/CD, scikit‑learn, TensorFlow, LangChain). Experience taking data science models from research and development into production. A strong understanding of Machine Learning approaches and algorithms and how they are monitored and maintained. Experience working within cloud environments would be beneficial (GCP a plus). Experience working within a regulated industry, ideally working in the London and Lloyd’s insurance markets. Bachelor’s Degree or higher in a STEM field. PhD in a STEM field is a plus.
What to expect during the recruitment process: Initial recruiter screening call, Interview with hiring manager, Technical Interview (this may vary depending on the role), Values Interview.
Data Scientist in London employer: Ki
Ki is an exceptional employer that fosters a dynamic and innovative work culture, where collaboration across diverse teams drives the development of cutting-edge insurance solutions. With a strong focus on employee growth, Ki offers opportunities to work with advanced technologies and methodologies in a fast-paced environment, all while being part of a pioneering company that is reshaping the insurance industry. Located in the heart of London, employees benefit from a vibrant city life and the chance to contribute to a rapidly growing global leader in algorithmic insurance.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist in London
✨Tip Number 1
Network like a pro! Reach out to current employees at Ki or similar companies on LinkedIn. A friendly chat can give you insider info and might just get your foot in the door.
✨Tip Number 2
Prepare for those interviews! Brush up on your machine learning knowledge and be ready to discuss how you've applied it in real-world scenarios. Practice explaining complex concepts in simple terms – it shows you really understand your stuff.
✨Tip Number 3
Show off your projects! If you've got any cool data science projects, make sure to highlight them during your interviews. Whether it's a GitHub repo or a personal blog, showcasing your work can set you apart from the crowd.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in being part of the Ki team.
We think you need these skills to ace Data Scientist in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Data Scientist role at Ki. Highlight your experience with machine learning, Python, and any relevant projects that showcase your skills in risk modelling and predictive analytics.
Craft a Compelling Cover Letter:Your cover letter should tell us why you're excited about joining Ki and how your background aligns with our mission. Be sure to mention any specific experiences that relate to working in agile teams or within regulated industries.
Showcase Your Technical Skills:In your application, don’t forget to highlight your hands-on experience with tools like TensorFlow, GitHub, and any cloud environments you've worked in. We want to see how you can contribute to our algorithmic underwriting team!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows us you’re keen on being part of the Ki team!
How to prepare for a job interview at Ki
✨Know Your Algorithms
Brush up on your knowledge of machine learning algorithms and risk modelling techniques. Be ready to discuss how you've applied these in past projects, especially in production environments. This will show that you understand the core of what Ki is doing.
✨Showcase Collaboration Skills
Since the role involves working with various teams, prepare examples of how you've successfully collaborated with product, engineering, or actuarial teams in the past. Highlight any cross-functional projects where you made a significant impact.
✨Prepare for Technical Questions
Expect technical questions related to Python, GitHub, and machine learning frameworks. Practise coding challenges or case studies that demonstrate your problem-solving skills and familiarity with tools like TensorFlow or scikit-learn.
✨Understand the Industry Context
Familiarise yourself with the insurance market, particularly the innovations Ki is bringing to the table. Being able to discuss how digital disruption is changing the industry will show your enthusiasm and alignment with Ki's mission.
