Actuarial Data Analyst

Ki Insurance; Greater London; Ibrido; GBP 60.000 - 90.000; Tempo pieno

Vantaggi offerti da questo lavoro

Competitive remuneration

Descrizione del lavoro

Ki Insurance is seeking an Actuarial Data Analyst to enhance data quality and usability across our actuarial function. You will partner with Pricing, Commercial Data, Reserving, and Portfolio Management to investigate data issues, improve analytics, and deliver actionable business insights for informed decision-making.

In this role you will translate complex data findings for diverse stakeholders while supporting continuous data governance and governance improvements across the actuarial

Competenze

• Proven experience as a data analyst in insurance or a data-intensive environment.
• Strong SQL skills and the ability to work with large, complex datasets.
• Familiarity with actuarial concepts and insurance data is highly desirable.
• Ability to translate data findings into clear insights for multiple stakeholders.

Mansioni

• Lead cross-divisional data analytics initiatives to improve pricing metrics and actuarial outputs.
• Support deep-dive analyses and reviews, scoping problems, assessing impact, and proposing solutions.
• Identify data gaps and improvements with the Commercial Data squad to inform roadmaps.
• Understand how Ki's data sets interrelate across Pricing, Reserving, and Portfolio Management.

Conoscenze

SQL

Python or R

Data analysis

Communication

Strumenti

Python

Descrizione del lavoro

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 Actuarial Data Analyst, you will play a key role in supporting the development and continuous improvement of our digital underwriting capability. You'll enhance the quality, credibility, and usability of data across our entire actuarial function. Sitting within our Pricing division, you'll partner closely with our Commercial Data, Reserving, and Portfolio Management teams to investigate data issues, improve analytical processes, and deliver valuable business insights. Acting as a vital connection between technical data specialists and actuarial stakeholders, you'll develop a holistic understanding of our data landscape and help empower informed decision-making. By combining your technical analytical skills with strong commercial understanding, you'll identify opportunities to enhance our data and make sure it is fit for purpose across all actuarial workflows. Your collaboration and commitment to continuous improvement will directly contribute to the effectiveness and scalability of the Ki platform.

What you will be doing:

• Lead and contribute to cross-divisional data analytics initiatives that improve the credibility and reliability of pricing metrics and actuarial outputs
• Support PLR and RARC deep-dive analysis and PMDR reviews, including investigation of data issues and bugs — scoping the problem, assessing severity and business impact, and proposing solutions
• Partner closely with the Commercial Data squad to identify key data gaps and areas for improvement, providing the actuarial business context needed to prioritise and shape their roadmap
• Develop and maintain a strong understanding of how Ki's data sets interrelate across Pricing, Reserving, and Portfolio Management, and act as a knowledge resource for the broader organisation
• Produce clear, accurate and insightful analysis that supports business understanding and commercial decision-making.
• Translate complex data findings into clear, actionable insights for both technical and non-technical stakeholders.
• Support the continuous improvement of data governance, analytical processes and reporting across the actuarial function.
• Build effective working relationships across the business to facilitate collaboration, knowledge sharing and delivery of strategic objectives.

• Proven experience as a data analyst, ideally within insurance, financial services, or a similarly data-intensive environment
• Familiarity with actuarial concepts and insurance data — exposure to pricing, reserving, or portfolio management workflows is highly desirable
• Strong SQL skills and comfort working with large, complex datasets; Python or R a plus
• Ability to investigate ambiguous data problems independently, form hypotheses, and communicate findings clearly
• Strong written and verbal communication skills. You will be working with a broad range of different stakeholders across different levels, so you’ll need to be able to effectively communicate complex technical concepts to different audiences.
• Unwavering curiosity and enthusiasm - to challenge how we do things and bring fresh ideas to the table. We’re always looking to improve!
• The ability to build effective working relationships within the team and across the wider business.
• A self-starting drive to succeed, ensuring delivery of your work to achieve our goals and meet deadlines.

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