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For Companies At a Glance
- Tasks: Lead data science projects, turning telematics data into actionable insights for insurance pricing.
- Company: Fast-growing tech company in the insurance sector with a focus on innovation.
- Benefits: Competitive salary, bonus, hybrid work model, and opportunities for professional growth.
- Why this job: Take ownership of impactful data products and shape the future of insurance pricing.
- Qualifications: Senior data science experience, strong Python skills, and a passion for innovation.
- Other info: Join a dynamic team with plans for expansion and career development.
The predicted salary is between 84000 - 132000 £ per year.
Working exclusively with my client, this role exists due to business expansion. The data science function launched in early 2023 and focuses on pricing and telematics driven products. The team already delivered over 20 percent profitability uplift across core insurance products using price optimisation models.
The role owns data structure and value extraction from large scale telematics data. The focus sits on turning driving behaviour into clear pricing and operational decisions for insurance products. The business operates a champion challenger framework. The team delivers frequent model improvements through strong code standards and repeatable processes. Work happens at pace and at scale.
What you will do:
- You will lead technical delivery across telematics data science.
- You will shape how data turns into pricing value and operational insight across the wider business.
Day to day responsibilities
- Design and deliver analytical solutions using telematics data
- Lead development of scoring and pricing algorithms
- Own end to end machine learning pipelines from data through production
- Work hands on with Python and Databricks
- Build repeatable and product agnostic training and serving frameworks
- Translate model outputs into clear guidance for pricing, operations, and finance
- Provide technical leadership and mentoring
- Challenge existing approaches within insurance pricing
- Take full ownership of delivery approach and outcomes
Technology environment
- Python
- Databricks
- Large scale and streaming data
- Spark or Kafka style processing
- Tree based models and deep neural networks
- Production grade machine learning systems
What my client look for
Essential experience
- Senior level data science delivery
- Large scale or time series data
- End to end machine learning delivery in production
- Strong Python engineering
- Solid statistical foundations
- Proven commercial impact from models delivered
Desirable experience
- Telematics or sensor based data
- Insurance or pricing domain exposure
- Experience leading small teams
- Evidence of idea generation and product thinking
What you will work on over the next 6 to 12 months
- Core telematics pricing models
- Expansion into fleet and taxi products
- New data driven insurance propositions
- Shaping long term data science strategy
- Building a team around this capability
Why join
This role offers full ownership of a high growth data product. The business doubled in size recently and plans further growth. You influence tooling, platforms, and technical direction. You build long term capability and there is an opportunity to grow a team further down the line.
Please apply for more information if this sounds like a role for you.
Lead Data Scientist in City of London employer: Maxwell Bond
Contact Detail:
Maxwell Bond Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Data Scientist in City of London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data science projects, especially those involving telematics or pricing models. This will give you an edge and demonstrate your hands-on experience to potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Be ready to discuss your experience with Python, machine learning pipelines, and any relevant projects you've worked on. Practice makes perfect!
✨Tip Number 4
Don't forget to apply through our website! We love seeing candidates who are genuinely interested in joining our team. Plus, it gives you a chance to stand out from the crowd and show us why you're the perfect fit for the Lead Data Scientist role.
We think you need these skills to ace Lead Data Scientist in City of London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV speaks directly to the role of Lead Data Scientist. Highlight your experience with telematics data, machine learning pipelines, and any relevant projects that showcase your skills in Python and data engineering.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're the perfect fit for this role. Share specific examples of how you've delivered impactful data science solutions in the past, especially in pricing or insurance domains.
Showcase Your Technical Skills: Don’t hold back on your technical prowess! Mention your experience with tools like Databricks, Spark, or Kafka, and any large-scale data projects you've worked on. We want to see your hands-on experience shine through.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity. Plus, it makes the process smoother for everyone!
How to prepare for a job interview at Maxwell Bond
✨Know Your Data Inside Out
Make sure you’re well-versed in the specifics of telematics data and how it can drive pricing decisions. Brush up on your experience with large-scale data processing and be ready to discuss how you've used Python and Databricks in past projects.
✨Showcase Your Leadership Skills
Since this role involves leading technical delivery, prepare examples that highlight your leadership experience. Think about times when you mentored a team or led a project, and be ready to explain how you foster collaboration and innovation.
✨Demonstrate Your Problem-Solving Approach
Be prepared to discuss how you tackle challenges in data science, especially in the context of insurance pricing. Use the STAR method (Situation, Task, Action, Result) to structure your answers and show how your solutions have had a commercial impact.
✨Familiarise Yourself with the Champion Challenger Framework
Understand the champion challenger framework and be ready to discuss how you would apply it in your role. Think of examples where you’ve implemented model improvements and how you ensure strong code standards and repeatable processes.
