At a Glance
- Tasks: Lead data enrichment strategies to enhance risk and pricing decisions in insurance.
- Company: Dynamic insurance company focused on innovation and analytics.
- Benefits: Hybrid work model, competitive salary, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on data quality and governance.
- Why this job: Make a real impact by solving complex business problems with data-driven insights.
- Qualifications: Experience in analytics or data science, strong SQL skills, and a numerical degree.
The predicted salary is between 60000 - 80000 £ per year.
Location: Peterborough or Manchester (hybrid)
About the Role: As a Data Development & Enrichment Lead, you will drive strategic use of enrichment data to support risk & retail pricing, lending decisions and acceptability. Sitting within the Analytics & Enrichment team, you support the development, maintenance and optimisation of the businesses data enrichment strategies across our insurance brands. This role blends hands-on analytics with leadership, stakeholder engagement and innovation in insurance enrichment to solve business problems and add commercial value.
Key Responsibilities:
- Identify opportunities for value creation: Proactively seek new ways to harvest value from new and existing enrichment from both internal and external sources.
- Creation of enrichment evaluation pipelines: develop methodologies for the continued evaluation of new and existing strategies.
- Partner with stakeholders: Collaborate with internal and external teams to understand their enrichment needs and work with 3rd parties to understand market opportunities.
- Champion analytics and enrichment across the business: Provide analytical support to the business, informing decision making.
- Own and optimise enrichment scorecards for the use of lending: Ensure models and processes are continuously refined for maximum effectiveness.
- Solve complex business problems: Apply creative approaches to tackle challenges and unlock insights.
- Design and enhance monitoring tools: Lead the development and optimisation of monitoring tools which keep an eye on existing enrichment strategies.
- Champion data quality and governance: Uphold high standards of data integrity, compliance, and governance across all analytical initiatives.
About you: Proven experience in pricing, analytics, data science, or a related field, within UK personal lines insurance market. Strong academic background in a numerical discipline (eg BSc Mathematics, Economics, Computer Science, Data Science). Experience of proactively identifying and solving complex business problems using data and/or implementing data orientated change that has delivered significant and measurable commercial benefit. Advanced SQL skills with experience with Python and/or R. Excellent communication and storytelling skills, with the ability to influence senior stakeholders. Strong organisational and strategic thinking capabilities.
Desirable: Experience with personal lines enrichment products including the use of credit bureau data. Exposure to A/B testing and optimisation techniques. Postgraduate qualification in relevant field (eg Computer Science, Data Science, Operational Research). Experience with modern data platforms (eg Databricks, Snowflake, MS Fabric).
Locations
Data Development & Enrichment Lead in Peterborough, Walton employer: Vermelo RPO
Join a forward-thinking company that values technical excellence and continuous improvement, where your expertise as a Large Loss Technical Controller will be pivotal in shaping high-value claims management. Our collaborative work culture fosters innovation and professional growth, offering you the chance to influence best practices while ensuring customer outcomes are protected. Located in a vibrant area, we provide a supportive environment that encourages career development and rewards your commitment to maintaining the highest standards in the industry.
StudySmarter Expert Advice🤫
We think this is how you could land Data Development & Enrichment Lead in Peterborough, Walton
✨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 Vermelo RPO!
✨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 Development & Enrichment Lead at Vermelo RPO.
✨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 Vermelo RPO.
✨Apply Directly through Our Website
When you find a suitable opening like Data Development & Enrichment Lead at Vermelo RPO, 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 Development & Enrichment Lead in Peterborough, Walton
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 Vermelo RPO, 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 Vermelo RPO. 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 Vermelo RPO
✨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 Vermelo RPO!
✨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.
