At a Glance
- Tasks: Optimise pricing strategies and develop innovative tools for motor insurance.
- Company: Leading insurer with a focus on data-driven decision-making.
- Benefits: Impressive salary, hybrid working, and opportunities for professional growth.
- Other info: Autonomous role with a dynamic environment and exciting career prospects.
- Why this job: Join a progressive team and make a real impact in the insurance industry.
- Qualifications: Experience in motor insurance pricing and proficiency in analytical tools like Python and SQL.
The predicted salary is between 60000 - 80000 £ per year.
Do you have very recent UK Insurance data experience? Hybrid working part City of London based. This leading and exciting Insurer are seeking a detail-oriented and organised Motor Insurance Pricing/Data Practitioner to join their Pricing and Underwriting team. To apply for this role you MUST have multiple years of experience working within a personal lines business within motor and or home products.
They’ve built the kind of pricing infrastructure every pricing professional aspires to work with:
- High-quality, accessible data
- A fast, flexible rating algorithm — deploy changes in hours
- Machine Learning Operations (MLOps) that enable fast, transparent, and controlled model development
- An operating model that gives complete autonomy to pricing professionals to dream up an idea and get it live
If you're passionate about using data, tech, and creativity to push the boundaries of insurance pricing, we’d love to hear from you.
Role Purpose
This role focuses on end-to-end customer pricing, covering both risk and margin for the Insurer. It is a highly autonomous role within a specialized team.
Key Responsibilities
- Optimization: Identify pricing opportunities across segments to maximize profitability and market competitiveness.
- Innovation: Develop new features, tools, and models for advanced pricing sophistication.
- Monitoring: Analyse claims performance to ensure accurate calibration, especially regarding inflation and trends.
- Automation: Build automated processes to improve operational efficiency.
Ideal Candidate Profile
- Extensive skills within Motor Insurance Pricing and Data
- Commercial Mindset: Motivated by driving tangible business value through data-driven decisions.
- Technical Proficiency: Skilled in data analysis and modelling techniques. Requires experience with analytical tools (e.g., Python, SQL, R) and a background in insurance pricing or data science.
The company are offering an impressive salary and benefits package and this is an exciting time to join this highly progressive Insurer.
MOTOR INSURANCE PRICING PRACTITIONER / DATA SCIENTIST in EC3A, Lime Street, Greater London employer: Energy Jobline CVL
Join a leading insurer in the heart of London, where innovation meets opportunity. With a strong focus on employee growth and a collaborative work culture, this company offers a hybrid working model that promotes work-life balance while providing access to high-quality data and cutting-edge technology. As a Motor Insurance Pricing Practitioner, you'll have the autonomy to drive impactful pricing strategies and contribute to a forward-thinking team dedicated to pushing the boundaries of insurance.
StudySmarter Expert Advice🤫
We think this is how you could land MOTOR INSURANCE PRICING PRACTITIONER / DATA SCIENTIST in EC3A, Lime Street, Greater London
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We think you need these skills to ace MOTOR INSURANCE PRICING PRACTITIONER / DATA SCIENTIST in EC3A, Lime Street, Greater London
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 Energy Jobline CVL, 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 Energy Jobline CVL. 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 Energy Jobline CVL
✨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 Energy Jobline CVL!
✨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.
