Senior Actuarial Analyst - Property

Lockton Companies
London
11 months ago
Applications closed

Related Jobs

View all jobs

Senior Pricing Anlayst

Senior Pricing Analyst - Halifax; Home Based

Director of Healthcare Analytics

Data Science Manager - Insurance (Propensity models)

Head of Underwriting Quality

Chief Risk Officer

As a Senior Actuarial Analyst you will work as part of the Risk Practices division to support our strategy to enhance Lockton’s use of analytics. You will support all divisions of Lockton giving you access to a wide variety of technical product lines & projects.

 

Recent team assignments include;

  • Working with the broking teams on client pricing work including using and adapting pricing models
  • Working with our client facing teams to build solutions for client questions or RFP’s using actuarial or data science techniques
  • Building apps to support client risk management – recent examples include benchmarking limits, risk calculations, comparing deal structures
  • Catastrophe and Natural Catastrophe modelling

 

Role Responsibilities:

  • Working with the Property broking teams to understand client needs and provide technical pricing input and where required, engage with Actuaries from Insurers to challenge their pricing assumptions, models and results
  • Reviewing the Property products and models and updating or adapting where required
  • Build new pricing models and update / adapt existing models
  • Undertake catastrophe modelling using RMS and/or AIR
  • Provide analytical model building support, such as Aggregate Loss Projections
  • Writing reports on the analytical data and model outputs to assist with commercial decision making
  • Provide actuarial and analytical support to business development opportunities and RFP requests 
  • Support the development of new products, initiatives and sales materials

Candidate Profile

  • You will be a part qualified Actuary with proven experience in General Insurance or Lloyd’s Market Insurance  
  • Previous experience of working in Property or property related business lines  
  • Proven ability to use RMS and/or AIR modelling
  • Proven experience of using R and R Shiny combined with strong Excel skills

 

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Jobs

Machine Learning Jobs in the Public Sector: Opportunities Across GDS, NHS, MOD, and More

Machine learning (ML) has rapidly moved from academic research labs to the heart of industrial and governmental operations. Its ability to uncover patterns, predict outcomes, and automate complex tasks has revolutionised industries ranging from finance to retail. Now, the public sector—encompassing government departments, healthcare systems, and defence agencies—has become an increasingly fertile ground for machine learning jobs. Why? Because government bodies oversee vast datasets, manage critical services for millions of citizens, and must operate efficiently under tight resource constraints. From using ML algorithms to improve patient outcomes in the NHS, to enhancing cybersecurity within the Ministry of Defence (MOD), there’s a growing demand for skilled ML professionals in UK public sector roles. If you’re passionate about harnessing data-driven insights to solve large-scale problems and contribute to societal well-being, machine learning jobs in the public sector offer an unparalleled blend of challenge and impact. In this article, we’ll explore the key reasons behind the public sector’s investment in ML, highlight the leading organisations, outline common job roles, and provide practical guidance on securing a machine learning position that helps shape the future of government services.

Jobs

Contract vs Permanent Machine Learning Jobs: Which Pays Better in 2025?

Machine learning (ML) has swiftly become one of the most transformative forces in the UK technology landscape. From conversational AI and autonomous vehicles to fraud detection and personalised recommendations, ML algorithms are reshaping how organisations operate and how consumers experience products and services. In response, job opportunities in machine learning—including roles in data science, MLOps, natural language processing (NLP), computer vision, and more—have risen dramatically. Yet, as the demand for ML expertise booms, professionals face a pivotal choice about how they want to work. Some choose day‑rate contracting, leveraging short-term projects for potentially higher immediate pay. Others embrace fixed-term contract (FTC) roles for mid-range stability, or permanent positions for comprehensive benefits and a well-defined career path. In this article, we will explore these different employment models, highlighting the pros and cons of each, offering sample take‑home pay scenarios, and providing insights into which path might pay better in 2025. Whether you’re a new graduate with a machine learning degree or an experienced practitioner pivoting into an ML-heavy role, understanding these options is key to making informed career decisions.

Jobs

Machine‑Learning Jobs for Non‑Technical Professionals: Where Do You Fit In?

The Model Needs More Than Math When ChatGPT went viral and London start‑ups raised seed rounds around “foundation models,” many professionals asked, “Do I need to learn PyTorch to work in machine learning?” The answer is no. According to the Turing Institute’s UK ML Industry Survey 2024, 39 % of advertised ML roles focus on strategy, compliance, product or operations rather than writing code. As models move from proof‑of‑concept to production, demand surges for specialists who translate algorithms into business value, manage risk and drive adoption. This guide reveals the fastest‑growing non‑coding ML roles, the transferable skills you may already have, real transition stories and a 90‑day action plan—no gradient descent necessary.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.