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- Tasks: Shape pricing strategies in telematics insurance using data analytics and statistical techniques.
- Company: Join a forward-thinking company in the telematics insurance sector.
- Benefits: Enjoy hybrid working, generous leave, bonuses, and exclusive discounts.
- Why this job: Make a real impact on pricing strategies while working with cutting-edge data tools.
- Qualifications: Degree in Maths, Stats, or related field; strong analytical skills required.
- Other info: Collaborative environment with opportunities for continuous learning and career growth.
The predicted salary is between 34000 - 42000 £ per year.
Telematics Pricing Analyst
Department: [SBL] Retail Pricing
Employment Type: Permanent – Full Time
Location: Bristol
Reporting To: Gareth Davies
Compensation: £40,000 – £50,000 / year
Description
The role focuses on customer engagement with telematics App and managing drivers’ telematics data to drive improvements in risk pricing while adhering to regulatory and market requirements.
What you\’ll be responsible for:
- Analyse historical data and trends to develop accurate pricing models and forecasts.
- Apply statistical and actuarial techniques to identify key risk factors influencing pricing decisions.
- Develop trading performance monitoring and predictions.
- Utilize insights from telemetry data, and customer App engagement to drive improvements in risk performance.
- Claims analysis and loss ratio performance monitoring (including projecting ultimate).
- Collaborate with pricing actuaries to design competitive pricing strategies aligned with the company’s financial objectives.
- Utilise insights from market research and competitor analysis to refine pricing recommendations.
- Present findings, insights and recommendations to senior management and stakeholders in a clear and impactful manner.
- Prepare and maintain detailed documentations of pricing models and methodologies.
- Present portfolio driving score movements and engagement levels.
- Work closely with Underwriting, Marketing and Claims teams to incorporate diverse perspectives into pricing decisions.
- Liaise with IT teams to implement pricing tools and system enhancements.
- Ensure pricing models and practices comply with relevant regulations and guidelines, including those issued by the Financial Conduct Authority (FCA).
- Contribute to the development and testing of customer engagement models.
- Explore and leverage machine learning tools to enhance predictive accuracy.
- Monitor the performance of pricing models, recommending updates as needed.
- Stay abreast of industry trends, emerging risks and technological advancements.
What you\’ll need:
- Bachelor’s degree in Mathematics, Statistics, Actuarial Science, Economics, or a related field is desirable, or a non-related degree which covers modules in data/coding or programming, for example.
- A passion for data, covering accuracy and integrity of data and driving actionable insights.
- Strong analytical and problem-solving skills with a high level of numerical proficiency.
- Knowledge of statistical software (e.g. R, Python, SQL) and data visualisation tools (e.g. PowerBI, Tableau).
- Familiarity with pricing techniques, including GLMs (Generalised Linear Models) and machine learning algorithms.
- Ability to interpret large, complex datasets and drive actionable insights.
- Excellent communication and presentation skills to convey technical findings to non-technical stakeholders.
- Teamwork and collaboration skills, with an aptitude for working across departments.
- Knowledge of insurance products, customer segments and market dynamics is desirable.
- Knowledge of telematics products, telemetry data and customer engagement analysis is desirable.
Our Benefits:
- Hybrid working – 2 days in the office and 3 days working from home
- 25 days annual leave, rising to 27 days over 2 years’ service and 30 days after 5 years’ service. Plus bank holidays!
- Discretionary annual bonus
- Pension scheme – 5% employee, 6% employer
- Flexible working – we will always consider applications for those who require less than the advertised hours
- Flexi-time
- Healthcare Cash Plan – claim cashback on a variety of everyday healthcare costs
- Electric vehicle – salary sacrifice scheme
- 100’s of exclusive retailer discounts
- Professional wellbeing, health & fitness app – Wrkit
- Enhanced parental leave, including time off for IVF appointments
- Religious bank holidays – if you don’t celebrate Christmas and Easter, you can use these annual leave days on other occasions throughout the year.
- Life Assurance – 4 times your salary
- 25% Car Insurance Discount
- 20% Travel Insurance Discount
- Cycle to Work Scheme
- Employee Referral Scheme
- Community support day
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Telematics Pricing Analyst employer: Somerset Bridge
Contact Detail:
Somerset Bridge Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Telematics Pricing Analyst
✨Tip Number 1
Network like a pro! Reach out to people in the telematics and insurance sectors on LinkedIn. A friendly message can go a long way, and you never know who might have the inside scoop on job openings.
✨Tip Number 2
Prepare for interviews by brushing up on your data analysis skills. Be ready to discuss how you've used statistical techniques in past roles. We want to see your passion for data shine through!
✨Tip Number 3
Showcase your communication skills! Practice explaining complex data insights in simple terms. This is key when presenting to non-technical stakeholders, so make sure you're comfortable with it.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are genuinely interested in joining our team.
We think you need these skills to ace Telematics Pricing Analyst
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Telematics Pricing Analyst role. Highlight your experience with data analysis, statistical techniques, and any relevant software skills. We want to see how your background aligns with what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about pricing strategies in the telematics insurance sector. Share specific examples of your analytical skills and how they can benefit us at StudySmarter.
Showcase Your Analytical Skills: In your application, don’t forget to showcase your analytical and problem-solving skills. Mention any experience you have with statistical software like R or Python, as well as your ability to interpret complex datasets. We love data-driven insights!
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of your application and ensures you don’t miss out on any important updates. Plus, it’s super easy!
How to prepare for a job interview at Somerset Bridge
✨Know Your Numbers
As a Telematics Pricing Analyst, you'll be dealing with data all day long. Brush up on your statistical techniques and be ready to discuss how you've used data analysis in past roles. Be prepared to explain your thought process when developing pricing models or forecasts.
✨Showcase Your Communication Skills
You'll need to present findings to senior management and stakeholders, so practice explaining complex data in simple terms. Think of examples where you've successfully communicated technical information to non-technical audiences, as this will demonstrate your ability to bridge the gap between data and decision-making.
✨Understand the Market
Familiarise yourself with the telematics insurance sector and current market trends. Research competitors and be ready to discuss how their pricing strategies might influence your recommendations. Showing that you understand the landscape will impress interviewers and highlight your proactive approach.
✨Collaborate and Innovate
This role requires teamwork across various departments. Prepare examples of how you've worked collaboratively in the past, especially in cross-functional teams. Also, think about innovative ideas you've contributed to projects, particularly those involving machine learning or customer engagement models.
