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- Tasks: Lead data science projects, transitioning pricing models to Python and developing machine learning capabilities.
- Company: QBE is a global insurer focused on enabling a resilient future with a supportive culture.
- Benefits: Enjoy 30 days holiday, flexible working, private medical insurance, and sustainable investing options.
- Why this job: Join a collaborative team, solve real-world problems, and make analytics part of everyday decisions.
- Qualifications: Expertise in Python, machine learning, and experience with large datasets required.
- Other info: This role is hybrid, based in London, and offers a chance to impact the insurance industry.
The predicted salary is between 43200 - 72000 £ per year.
At QBE, our purpose is to enable a more resilient future. We are an international insurer and reinsurer with a local presence in 27 countries.
We are seeking a data science lead to join our established and growing pricing and analytics team for Automotive Protection's global business on a fixed-term basis for 12 months. This is an exciting opportunity for an individual looking to start or continue their career within the insurance industry, and who wants to join a team of experienced and supportive colleagues. This role will be based in our London office.
In this role, you will apply data science and modelling techniques to solve real-world business challenges and support data-driven decision-making. Partnering with the Global Head of Performance and Senior Analyst Manager, you'll be responsible for transitioning our pricing models to Python and developing our machine learning capability.
Main responsibilities:
- Lead in transitioning our GLM pricing models to Python and developing our machine learning capability
- Help shape and support Automotive Protection's data science strategy
- Work closely with the Global Head of Performance and Senior Analyst Manager to identify opportunities, plan project delivery and deliver key outcomes that drive decision-making
- Develop and implement analytical models that support pricing, identify fraud, improve retention and renewals, and drive profitable growth
- Collaborate with analyst team to build, monitor, and refresh predictive models as needed
- Design and enhance analytics that drive business insights and decisions
- Ensure models meet regulatory standards and are well documented
- Present findings clearly and confidently to different audiences, making sure insights are well understood and actionable
- Collaborate across functions, including with clients, senior stakeholders, and various business teams
This role is ideal for someone who enjoys solving real-world problems with data, takes ownership of their work, and is passionate about making analytics part of everyday business decisions.
About You: You're a hands-on data scientist who enjoys solving real problems with data. You're confident using Python, comfortable working with large and complex datasets, and able to explain your work clearly to people from all kinds of backgrounds. You work well with others, think creatively, and enjoy helping bring new ideas to life.
Skills you'll need:
- Expert in Python for data analysis, modelling, and building solutions
- Familiarity with working in a Linux environment
- Strong understanding of machine learning and data science
- Good experience in MS SQL Server Management Studio, MS Office, Power BI, and Excel, with the ability to transform data into impactful insights
- A background in data management or analytics within financial services, ideally in general insurance
- A history of developing models that have led to real, lasting business improvements
- Experience working with large datasets, including both structured and unstructured data
- Skilled at defining customer requirements, solving complex problems, and delivering tailored solutions
- The ability to explain technical topics clearly to non-technical colleagues and stakeholders
- A collaborative, open approach to working with others and building relationships
- Experience working in fast-paced environments and managing projects using agile ways of working
Why QBE? At My Best: At QBE, we want our people to feel rewarded and inspired to perform at their best, that's why we have created "At My Best". It's our connection, our way of showing we have your back. We understand that one size doesn't fit all and that priorities can change depending on your life stage. That is why our blend of wellbeing initiatives and benefits offer flexibility to suit what matters most to you. It's in the culture of our business, our QBE DNA, to support our people.
To find out more about why you should work for QBE, visit our careers website.
What next? If you have a passion to contribute to QBE's vision of enabling a more resilient future for our customers and the community, we encourage you to apply! Simply click the "apply" button to submit your CV and other relevant documents, and a member of our friendly Talent Acquisition team will be in contact to discuss your interest further if you meet the requirements of the role.
We believe this is our moment - what if it was yours too? APPLY NOW and let's make it happen!
Data Science Lead employer: QBE Insurance Group Limited
Contact Detail:
QBE Insurance Group Limited Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Science Lead
✨Tip Number 1
Familiarise yourself with the latest trends in data science and machine learning, especially as they relate to the insurance industry. This will not only help you understand the role better but also allow you to engage in meaningful conversations during interviews.
✨Tip Number 2
Network with professionals in the insurance and data science fields. Attend relevant meetups or webinars, and connect with current employees at QBE on platforms like LinkedIn to gain insights into the company culture and expectations.
✨Tip Number 3
Prepare to discuss specific projects where you've successfully applied Python for data analysis or machine learning. Be ready to explain your thought process and the impact of your work, as this will demonstrate your hands-on experience and problem-solving skills.
✨Tip Number 4
Showcase your ability to communicate complex data concepts clearly. Practice explaining your previous work to non-technical audiences, as this skill is crucial for collaborating with various stakeholders at QBE.
We think you need these skills to ace Data Science Lead
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data science, particularly with Python and machine learning. Emphasise any previous roles where you've led projects or collaborated with teams, as this aligns with the responsibilities of the Data Science Lead position.
Craft a Compelling Cover Letter: In your cover letter, express your passion for data science and how it can drive business decisions. Mention specific examples of how you've solved real-world problems using data, and explain why you're excited about the opportunity at QBE.
Showcase Your Technical Skills: Clearly outline your technical skills in Python, SQL, and machine learning in both your CV and cover letter. Provide examples of projects where you've successfully applied these skills, especially in a financial services context.
Prepare for Interviews: If you get an interview, be ready to discuss your past experiences in detail. Prepare to explain complex technical concepts in simple terms, as you'll need to communicate effectively with non-technical stakeholders at QBE.
How to prepare for a job interview at QBE Insurance Group Limited
✨Showcase Your Python Skills
As a Data Science Lead, you'll need to demonstrate your expertise in Python. Be prepared to discuss specific projects where you've used Python for data analysis and modelling. Highlight any experience transitioning models to Python, as this is a key responsibility of the role.
✨Prepare for Technical Questions
Expect technical questions related to machine learning and data science. Brush up on your knowledge of algorithms, model evaluation, and data handling techniques. Being able to explain complex concepts in simple terms will impress your interviewers.
✨Demonstrate Collaborative Spirit
This role requires working closely with various teams and stakeholders. Share examples of how you've successfully collaborated in past projects. Emphasise your ability to communicate effectively with both technical and non-technical colleagues.
✨Understand the Business Context
Familiarise yourself with the insurance industry and QBE's business model. Be ready to discuss how data science can drive decision-making and improve business outcomes in this context. Showing that you understand the bigger picture will set you apart from other candidates.
