At a Glance
- Tasks: Develop machine learning models and analyse data to enhance underwriting decisions.
- Company: Join QBE, a global insurer with a human touch and innovative culture.
- Benefits: Enjoy 30 days holiday, flexible working, private medical insurance, and a generous pension plan.
- Other info: Dynamic team environment with opportunities for career growth and development.
- Why this job: Make a real impact using data science in the exciting world of insurance.
- Qualifications: Experience in pricing, statistical modelling, or machine learning with strong Python skills.
The predicted salary is between 63000 - 77000 £ per year.
At QBE, we get to the heart of what matters for our customers. We're an international insurer with more than 13,000 people working across 26 countries. It's an exciting time as we're building momentum towards our vision to become the most consistent and innovative risk partner.
Join QBE Portfolio Solutions (QPS) in our Scout: Research & Insights team. You will use pricing, data science and machine learning to improve underwriting and portfolio decisions. We welcome candidates from either an insurance pricing or actuarial background, or a data science and machine learning background.
Your New Role:
- Develop pricing, statistical and machine-learning models for underwriting and portfolio decisions.
- Analyse policy, exposure, claims and pricing data to identify trends, risks and opportunities.
- Build reusable solutions using Python, SQL and Databricks.
- Apply sound ML engineering practices so models are reproducible, tested, maintainable and ready to operationalise.
- Work with underwriting, pricing, catastrophe modelling, Data & AI and engineering teams to turn business questions into scalable solutions.
- Communicate complex analysis as clear insights and recommendations for technical and non-technical stakeholders.
About You:
You may bring experience from either of the following routes:
- Pricing or actuarial: commercial insurance pricing, portfolio analytics, GLMs, rate adequacy, risk selection or portfolio performance, supported by strong analytical and coding skills.
- Data science or machine learning: predictive modelling, feature engineering, ML pipelines, workflow automation or MLOps, ideally using Python, SQL and Databricks.
What You Will Bring:
- Strong analytical and problem-solving skills, with practical experience in pricing, statistical modelling or machine learning.
- Strong Python skills and confidence working with data; SQL experience is highly desirable.
- Knowledge of reproducibility, testing, version control and good software or ML engineering practices.
- Ability to work with technical teams and business stakeholders and explain complex analysis clearly.
- Interest in applying machine learning to real commercial problems.
- Experience in commercial or specialty insurance would be an advantage.
Benefits:
- 30 days holiday a year with the option to buy up to 2 additional days.
- Flexible working opportunities including part-time, job share and compressed hours.
- Pension plan with employer contributions of 10% of your basic salary.
- Private medical insurance for you and your family.
- Family friendly policies offering 26 weeks leave at full pay regardless of gender identity, sexual orientation or how you become a parent.
- Short term remote work abroad - request up to 20 days per year to work remotely from certain locations abroad.
- Sustainable investing supporting net-zero goals.
- Cycle-to-Work scheme.
Awards & Recognition:
We value our employee's experience and are proud to have been recognised for various awards.
How to Apply:
To submit your application, click "Apply" and follow the step by step process.
Equal Employment Opportunity: QBE is an equal opportunity employer and complies with equal employment opportunity legislation in each jurisdiction it operates.
Data Scientist - QPS in London employer: QBE Insurance Group
At QBE, we pride ourselves on being an excellent employer, offering a dynamic work culture that fosters collaboration and innovation. Our London-based IT Business Analyst role provides not only competitive benefits such as flexible working arrangements and generous holiday allowances but also ample opportunities for professional growth within a supportive team environment. Join us to make a meaningful impact in the insurance industry while enjoying a strong commitment to sustainability and employee well-being.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist - QPS in London
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like QBE Insurance Group!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Data Scientist - QPS at QBE Insurance Group.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like QBE Insurance Group.
✨Apply Directly through Our Website
When you find a suitable opening like Data Scientist - QPS at QBE Insurance Group, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Data Scientist - QPS in 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 QBE Insurance Group, 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 QBE Insurance Group. 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 QBE Insurance Group
✨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 QBE Insurance Group!
✨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.
