Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Data Scientist (Insurance)

Lloyd's
London
8 months ago
Applications closed

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Lloyd’s is the world’s leading insurance and reinsurance marketplace. We share the collective intelligence and risk sharing expertise of the market’s brightest minds, working together for a braver world.

Our role is to inspire courage, so tomorrow’s progress isn’t limited by today’s risks.

Our shared values: we are brave; we are stronger together; we do the right thing; guide what we do and how we act. If you share our values and our passion to build a future that’s more sustainable, resilient and inclusive, you’ll find a home at Lloyd’s – build a braver future with us.

Lloyd’s is seeking to recruit a Data Scientist (Insurance) to deliver analytics, tools and insights to enable effective risk-based oversight and drive continuous improvement in market performance.

Principal Accountabilities

  1. Work with the Senior Manager and colleagues in Portfolio Analytics to develop methodologies, tools and controls that allow Lloyd’s to efficiently and effectively oversee the market.
  2. Lead analytical and data related projects that help manage the performance of the Lloyd’s market.
  3. Develop new methods for understanding performance to enable better forward-looking assessments.
  4. Develop methods of measuring and targeting a sustainable portfolio mix for Lloyd’s taking into account risk vs reward and the Market’s strategic direction.
  5. Drive increased insight of Lloyd’s portfolio composition and identify areas for oversight and opportunity through quantification, modelling and original analysis and further development of the Lloyd’s Model Portfolio.
  6. Help Portfolio Analytics to become the go-to place for data and analytics in Markets.
  7. Act as data subject matter expert for the market data returns used by Underwriting to assess performance.
  8. Lead on initiatives to improve data quality, insight, alignment and rationalisation across Underwriting.
  9. Manage and lead the automation of quarterly BAU processes:
  10. Risk Based Oversight – which analyses performance trends by class of business.
  11. Underwriting Risk Appetite reporting which monitors whole market performance.
  12. MI for Markets Executives.
  13. Contribute to cross-functional collaboration, in particular with Finance, Predictive Analytics, Capital and Data.

Skills Knowledge and Experience

  1. Intermediate to advanced knowledge of statistical and data science techniques including modern statistical languages such as R and Python.
  2. Data manipulation and analysis in R and/or Python.
  3. Building visualisation tools such as Qliksense, Tableau and/or Power BI.
  4. Understanding of analytical methods and up to date knowledge of data science.
  5. Solid insurance knowledge including Lloyd’s, London Market & International Markets.
  6. Engagement with senior stakeholders and managing expectations.
  7. Driving change, building models, introducing controls, improving processes, implementing systems, encouraging adoption and working cross functionally.
  8. Established analytical and quantitative capabilities; programming and data modelling skills.
  9. Ability to problem solve and identify and implement process improvements.
  10. Time management and communication skills to effectively field competing priorities.

Diversity and inclusion are a focus for us – Lloyd’s aim is to build a diverse, inclusive environment that reflects the global markets we work in. One where everyone is treated with dignity and respect to achieve their full potential. In practice, this means we are positive and inclusive about making workplace adjustments, we offer regular health and wellbeing programmes, diversity and inclusion training, employee networks, mentoring and volunteering opportunities as well as investment into your professional development.

We understand that our work/life balance is important to us all and that a hybrid of working from the office and home can offer a great level of flexibility. Flexible working forms part of a total reward approach which offers a host of other benefits over and above the standard offering (generous pension, healthcare, wellbeing etc). These include financial support for training, education & development, a benefit allowance (to spend on our flexible benefits such as gym membership, dental insurance, extra holiday or to partake in our cycle to work scheme), employee recognition scheme and various employee discount schemes.

By choosing Lloyd's, you'll be part of a team that brings together the best minds in the industry, and together with our underwriters and brokers, we create innovative, responsive solutions allowing us to share risk and solve complex problems.

Should you require any additional support with your application, or any adjustments, please click the following link:

https://cleartalents.com/apply/lloyds-msa1645695881

Please note, clicking on this link does not register your application for the vacancy.

#J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

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

Industry Insights

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

Neurodiversity in Machine Learning Careers: Turning Different Thinking into a Superpower

Machine learning is about more than just models & metrics. It’s about spotting patterns others miss, asking better questions, challenging assumptions & building systems that work reliably in the real world. That makes it a natural home for many neurodivergent people. If you live with ADHD, autism or dyslexia, you may have been told your brain is “too distracted”, “too literal” or “too disorganised” for a technical career. In reality, many of the traits that can make school or traditional offices hard are exactly the traits that make for excellent ML engineers, applied scientists & MLOps specialists. This guide is written for neurodivergent ML job seekers in the UK. We’ll explore: What neurodiversity means in a machine learning context How ADHD, autism & dyslexia strengths map to ML roles Practical workplace adjustments you can ask for under UK law How to talk about neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in ML – & how to turn “different thinking” into a genuine career advantage.

Machine Learning Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we move into 2026, the machine learning jobs market in the UK is going through another big shift. Foundation models and generative AI are everywhere, companies are under pressure to show real ROI from AI, and cloud costs are being scrutinised like never before. Some organisations are slowing hiring or merging teams. Others are doubling down on machine learning, MLOps and AI platform engineering to stay competitive. The end result? Fewer fluffy “AI” roles, more focused machine learning roles with clear ownership and expectations. Whether you are a machine learning job seeker planning your next move, or a recruiter trying to build ML teams, understanding the key machine learning hiring trends for 2026 will help you stay ahead.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.