Real-Time Data Engineer for Algorithmic Insurance Platform in London

Real-Time Data Engineer for Algorithmic Insurance Platform in London

London Full-Time 63000 - 77000 £ / year (est.) No working from home possible
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At a Glance

  • Tasks: Build and maintain data pipelines for real-time insights in algorithmic insurance.
  • Company: Ki, a forward-thinking company revolutionising the insurance industry.
  • Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
  • Other info: Collaborate with experts in a fast-paced, supportive environment.
  • Why this job: Join a dynamic team and shape the future of insurance with data-driven solutions.
  • Qualifications: Experience in data engineering and a passion for innovative technology.

The predicted salary is between 63000 - 77000 £ per year.

Ki is building an agile data-enabled platform for algorithmic insurance in the UK. You will join the commercial performance insights squad to monitor real-time performance of our algorithmically underwritten business and upgrade the data foundation to unlock faster, more reliable insights across customer-facing products.

You will collaborate with actuaries, data scientists and engineers to design, build, and maintain production-grade data pipelines, data models and the supporting infrastructure.

Real-Time Data Engineer for Algorithmic Insurance Platform in London employer: Ki

Ki in London is an exceptional employer that fosters a collaborative work culture, where employees are encouraged to innovate and grow. With a focus on professional development, you will have access to numerous training opportunities and the chance to work alongside industry experts in a dynamic environment. The company's commitment to regulatory excellence and its strategic location in London make it an attractive place for those seeking meaningful and rewarding careers in capital modelling.

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Contact Details:

Ki Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Real-Time Data Engineer for Algorithmic Insurance Platform in London

Get Involved in Data Science Meetups

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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 Real-Time Data Engineer for Algorithmic Insurance Platform at Ki.

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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.

Apply Directly through Our Website

When you find a suitable opening like Real-Time Data Engineer for Algorithmic Insurance Platform at Ki, 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 Real-Time Data Engineer for Algorithmic Insurance Platform in London

Real-Time Data Processing
Data Pipeline Development
Data Modelling
Infrastructure Maintenance
Collaboration with Actuaries
Collaboration with Data Scientists
Collaboration with Engineers

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, 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. 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

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!

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.