Pricing Manager Motor & Home

Gerrard White
Rusholme
1 year ago
Applications closed

Related Jobs

View all jobs

Senior Data Scientist – Home Insurance Pricing & ML (Hybrid)

Manager - Data and Data Science Strategy - Emerging Data and Capabilities

Manager - Data and Data Science Strategy - Emerging Data and Capabilities

Machine Learning Engineer (Manager)

Machine Learning Engineer (Manager)

Machine Learning Engineer (Manager)

Pricing Manager Motor, Home, Personal Lines, General Insurance £70,000 - £90,000 Bonus Benefits Location: South East UK or Manchester (Flexible Hybrid Working) Role Overview: We are looking for a Pricing Manager to join a rapidly growing pricing department, working across multiple insurance lines. As a key player, you'll drive innovation in pricing techniques, develop advanced data models, and support both motor and home product pricing. This role will suit an experienced Pricing Manager looking for a new challenge or a Senior Pricing Analyst / Lead Pricing Analyst with experience mentoring junior team members ready for a step up. Key Responsibilities: Maintain and enhance pricing models using both traditional and data science techniques. Advance the adoption of statistical methods to improve pricing accuracy and efficiency. Develop automated reporting structures to monitor pricing performance. Collaborate closely with pricing, underwriting, and data science teams to drive innovation. Manage, coach, and mentor a team, fostering a culture of excellence. Communicate insights to key stakeholders and facilitate data-driven decision-making.Key Skills & Experience: Experience managing insurance pricing teams (motor or home insurance knowledge preferred). Familiarity with predictive modelling techniques such as Logistic Regression, GBMs, Decision Trees, Neural Nets. Proficiency in programming languages like R or Python with SAS and SQL. Experience with Radar software is preferred. Strong communication and leadership skills, with a passion for process innovation.Behaviours: Motivated, self-starter with a drive to learn and grow. Logical thinker with a positive, professional attitude. Passionate about challenging the norm and improving processes.If you are an experienced pricing professional with a drive for innovation, we'd love to hear from you Apply now and help shape the future of insurance pricing. PricingManager InsuranceCareers DataScience JobOpportunity HiringNow

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.

Machine Learning Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Are you considering a career change into machine learning in your 30s, 40s or 50s? You’re not alone. In the UK, organisations across industries such as finance, healthcare, retail, government & technology are investing in machine learning to improve decisions, automate processes & unlock new insights. But with all the hype, it can be hard to tell which roles are real job opportunities and which are just buzzwords. This article gives you a practical, UK-focused reality check: which machine learning roles truly exist, what skills employers really hire for, how long retraining realistically takes, how to position your experience and whether age matters in your favour or not. Whether you come from analytics, engineering, operations, research, compliance or business strategy, there is a credible route into machine learning if you approach it strategically.

How to Write a Machine Learning Job Ad That Attracts the Right People

Machine learning now sits at the heart of many UK organisations, powering everything from recommendation engines and fraud detection to forecasting, automation and decision support. As adoption grows, so does demand for skilled machine learning professionals. Yet many employers struggle to attract the right candidates. Machine learning job adverts often generate high volumes of applications, but few applicants have the blend of modelling skill, engineering awareness and real-world experience the role actually requires. Meanwhile, strong machine learning engineers and scientists quietly avoid adverts that feel vague, inflated or confused. In most cases, the issue is not the talent market — it is the job advert itself. Machine learning professionals are analytical, technically rigorous and highly selective. A poorly written job ad signals unclear expectations and low ML maturity. A well-written one signals credibility, focus and a serious approach to applied machine learning. This guide explains how to write a machine learning job ad that attracts the right people, improves applicant quality and strengthens your employer brand.

Maths for Machine Learning Jobs: The Only Topics You Actually Need (& How to Learn Them)

Machine learning job adverts in the UK love vague phrases like “strong maths” or “solid fundamentals”. That can make the whole field feel gatekept especially if you are a career changer or a student who has not touched maths since A level. Here is the practical truth. For most roles on MachineLearningJobs.co.uk such as Machine Learning Engineer, Applied Scientist, Data Scientist, NLP Engineer, Computer Vision Engineer or MLOps Engineer with modelling responsibilities the maths you actually use is concentrated in four areas: Linear algebra essentials (vectors, matrices, projections, PCA intuition) Probability & statistics (uncertainty, metrics, sampling, base rates) Calculus essentials (derivatives, chain rule, gradients, backprop intuition) Basic optimisation (loss functions, gradient descent, regularisation, tuning) If you can do those four things well you can build models, debug training, evaluate properly, explain trade-offs & sound credible in interviews. This guide gives you a clear scope plus a six-week learning plan, portfolio projects & resources so you can learn with momentum rather than drowning in theory.