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?

As our Associate Data Scientist, you’ll join our Algorithmic Underwriting team, helping us build and enhance the machine learning models that power the Ki platform’s digital underwriting and portfolio management. Working under the guidance of senior colleagues, you’ll carry out data analysis and model development that directly improves how we assess risk, and grow your skills through our data science community and talent framework.

What you will be doing: 🖋️

Delivery and technical

• Contribute to the build and improvement of Ki’s machine learning models for risk assessment, under the guidance of senior colleagues.
• Conduct exploratory analysis of internal and external datasets to identify opportunities to improve the algorithm.
• Support the monitoring and evaluation of live models, learning how models are operated safely in production.

Commercial and stakeholder

• Work closely with the Portfolio Underwriting team to understand the commercial context of technical work and ensure solutions deliver real-world value.
• Communicate findings clearly to technical and non-technical audiences.

People and discipline

• Participate actively in Ki’s data science community, developing technical skills in line with the talent framework.

Governance and risk

• Follow Ki’s model governance and documentation standards in all work.

Requirements

Proficiency in Python and common machine learning frameworks such as scikit-learn.

• Strong analytical capability to evaluate models and explore complex datasets.
• Bachelor’s degree or higher in a STEM field, or equivalent demonstrable practical experience.
• Familiarity with cloud environments, particularly Google Cloud Platform (GCP).
• Exposure to SQL and software engineering practice (version control, testing).
• Interest in insurance or financial services.
• Excellent communication skills, written and verbal, especially in sharing technical concepts with broader audiences.
• Strong interpersonal skills, including teamwork, facilitation and planning.
• Pro-active, self-motivated and able to use own initiative.
• Excellent analytical and technical skills.
• Picks up new technologies and business domains quickly.

Benefits

You’ll get a highly competitive remuneration and benefits package. This is kept under constant review to make sure it stays relevant. We understand the power of saying thank you and take time to acknowledge and reward extraordinary effort by teams or individuals.

What to expect during the recruitment process:

1. Initial recruiter screening call
2. Interview with hiring manager
3. Technical Interview (this may vary depending on the role)
4. Values Interview