At a Glance
- Tasks: Join our team to enhance machine learning models for digital underwriting and risk assessment.
- Company: Ki, a pioneering global algorithmic insurance carrier with a mission to disrupt the industry.
- Benefits: Competitive salary, recognition for hard work, and a dynamic work environment.
- Other info: Collaborative culture with opportunities for professional growth and skill development.
- Why this job: Make a real impact in a fast-growing company using cutting-edge technology.
- Qualifications: Proficiency in Python, strong analytical skills, and a STEM degree or equivalent experience.
The predicted salary is between 63000 - 77000 £ 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?
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.
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
- Initial recruiter screening call
- Interview with hiring manager
- Technical Interview (this may vary depending on the role)
- Values Interview
- #J-18808-Ljbffr
Associate Data Scientist employer: Ki Insurance
Ki Insurance is an exceptional employer, offering a dynamic work environment in the heart of London that fosters collaboration and innovation. With a strong focus on employee development, we provide ample opportunities for growth within the marine insurance sector, alongside competitive benefits and a supportive culture that values teamwork and excellence. Join us to be part of a forward-thinking company that prioritises your professional journey while making a meaningful impact in the industry.
StudySmarter Expert Advice🤫
We think this is how you could land Associate Data Scientist
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Ki Insurance!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Associate Data Scientist at Ki Insurance.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Ki Insurance.
✨Apply Directly through Our Website
When you find a suitable opening like Associate Data Scientist 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 Associate Data Scientist
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.
