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For Companies At a Glance
- Tasks: Join us as a Data Scientist to enhance our algorithm for better risk assessment.
- Company: Ki is revolutionizing the insurance tech industry with innovative solutions since 2021.
- Benefits: Enjoy competitive pay, recognition for your efforts, and a diverse, inclusive culture.
- Why this job: Be part of a groundbreaking team solving unique industry challenges in a supportive environment.
- Qualifications: Experience with machine learning frameworks and cloud environments is essential.
- Other info: We value diversity and encourage everyone to bring their authentic selves to work.
The predicted salary is between 43200 - 72000 £ per year.
Who are we?
Ki is the biggest global insurance tech company you’ve never heard of, unless you’ve been looking to insure a satellite, wind farm or music festival recently.
Having written over $877m in gross written premium in 2023, we’ve achieved significant growth since our beginnings in 2021. Our investors were excited about the fact we were revolutionising the way a 333 year-old industry was working. There are hardly any industries left that are mainly paper based, but the specialty insurance market is one. Together with partners at Google and UCL we developed Ki and created a platform that helps insurance brokers place risk in a fast and frictionless way. We’re continuing to lead the charge on the digitisation of this market and we need more excellent minds to work with us to realise this goal and create more opportunities.
What you will be working on
We’re looking for a Data Scientist to join our team, where you’ll enable Ki’s algorithm to learn from data in order to better carry out underwriting and portfolio management capabilities, whilst owning the delivery of individual machine learning models to help Ki better assess and manage risk.
Fully utilizing your experience with common machine learning frameworks (e.g. scikit-learn, TensorFlow, etc.) as well as any experience you have working in cloud environments (GCP would be great!) and your understanding of Machine Learning approaches, algorithms and how they are monitored and maintained.
You’ll join a team on an exciting journey – we’re solving industry problems that have never been solved before.
Our culture
Inclusion & Diversity is at the heart of our business at Ki. We recognise that diversity in age, race, gender, ethnicity, sexual orientation, physical ability, thought and social background bring richness to our working environment. No matter who you are, where you’re from, how you think, or who you love, we believe you should be you.
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.
If this sounds like a role and a culture that appeals to you, let us know – apply here.
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Data Scientist employer: Ki Insurance
Contact Detail:
Ki Insurance Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist
✨Tip Number 1
Familiarize yourself with the specific machine learning frameworks mentioned in the job description, like scikit-learn and TensorFlow. Having hands-on experience with these tools will not only boost your confidence but also demonstrate your technical skills during discussions.
✨Tip Number 2
Since Ki emphasizes cloud environments, particularly GCP, consider working on personal projects or contributing to open-source projects that utilize Google Cloud. This practical experience can set you apart from other candidates.
✨Tip Number 3
Engage with the insurance tech community online. Follow relevant blogs, join forums, and participate in discussions about digitization in the insurance industry. This will help you understand current trends and challenges, which you can reference in your conversations.
✨Tip Number 4
Highlight your understanding of inclusion and diversity in your interactions. Ki values a diverse workplace, so sharing your thoughts on how diversity enhances team performance can resonate well with their culture.
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Understand the Company: Familiarize yourself with Ki and its mission in the insurance tech industry. Highlight your understanding of their innovative approach to digitizing a traditionally paper-based market in your application.
Showcase Relevant Experience: Emphasize your experience with machine learning frameworks like scikit-learn and TensorFlow. Mention any projects or roles where you utilized these skills, especially in cloud environments like GCP.
Highlight Problem-Solving Skills: Discuss specific examples where you've solved complex problems using data science. This could include developing algorithms or models that improved risk assessment or portfolio management.
Express Alignment with Company Culture: Ki values inclusion and diversity. Make sure to convey how your background and experiences align with their culture. Share any relevant experiences that demonstrate your commitment to these values.
How to prepare for a job interview at Ki Insurance
✨Showcase Your Machine Learning Expertise
Be prepared to discuss your experience with machine learning frameworks like scikit-learn and TensorFlow. Highlight specific projects where you've successfully implemented these technologies, focusing on the impact they had on the outcomes.
✨Demonstrate Your Understanding of Risk Assessment
Since the role involves underwriting and portfolio management, be ready to explain how you approach risk assessment. Discuss any relevant methodologies or algorithms you've used in past projects to manage and assess risk effectively.
✨Familiarize Yourself with Cloud Environments
If you have experience with cloud platforms, especially GCP, make sure to mention it. Discuss how you've utilized cloud environments in your previous work to enhance data processing and model deployment.
✨Emphasize Inclusion & Diversity
Ki values diversity, so be sure to express your commitment to an inclusive workplace. Share any experiences you have that demonstrate your ability to work collaboratively with diverse teams and how you contribute to a positive team culture.
