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, dynamic work environment, and opportunities for professional growth.
- Other info: Collaborative culture with a focus on innovation and career development.
- Why this job: Be part of a fast-growing company making a real impact in the insurance market.
- 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 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
✨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 even lead to a referral, which is always a bonus!
✨Tip Number 2
Prepare for those interviews! Brush up on your machine learning algorithms and be ready to discuss how you've applied them in real-world scenarios. Practice explaining complex concepts in simple terms – it shows you really know your stuff.
✨Tip Number 3
Show off your projects! If you've got any cool data science projects or contributions to open-source, make sure to highlight them. Having a portfolio can set you apart and demonstrate your hands-on experience.
✨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
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Data Scientist role at Ki. Highlight your hands-on 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 to disrupt the insurance market. Be sure to mention any experience you have in agile environments or working with cross-functional teams.
Showcase Your Technical Skills:In your application, don’t forget to highlight your technical skills, especially in Python and any machine learning frameworks you've used. We want to see how you’ve taken models from research to production, so share specific examples!
Apply Through Our Website:We encourage you to apply through our website for the best chance of getting noticed. It’s the easiest way for us to keep track of your application and ensure it reaches the right people!
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 Your 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, machine learning frameworks, and cloud environments. Brush up on your coding skills and be ready to solve problems on the spot. Practising common data science interview questions can really help.
✨Understand the Company’s Mission
Familiarise yourself with Ki's mission to disrupt the insurance market. Think about how your skills and experiences align with their goals. Being able to articulate why you want to work there and how you can contribute will set you apart.
