At a Glance
- Tasks: Analyse and configure insurance pricing models to drive client success.
- Company: Join Ignite Systems, a leader in innovative insurance technology.
- Benefits: Flexible working options, competitive salary, and opportunities for professional growth.
- Other info: Collaborative team environment with a focus on innovation and client solutions.
- Why this job: Make a real impact by solving complex data challenges in the insurance sector.
- Qualifications: Strong analytical skills and experience with data interpretation required.
The predicted salary is between 35000 - 45000 £ per year.
At Ignite Systems, we help insurers and brokers work smarter through innovative technology, data, and automation solutions. As we continue to grow, we're looking for a Data Analyst to join our team and play a key role in supporting and enhancing insurance scheme pricing models, configurations, and client solutions. This is an excellent opportunity for someone who enjoys working with data, solving complex problems, and collaborating with clients to deliver meaningful business outcomes.
Responsibilities
- Analyze and interpret pricing data, rules, and algorithms to support scheme performance and profitability.
- Configure and maintain pricing structures within our systems.
- Investigate scheme queries and implement agreed changes on behalf of clients.
- Work closely with internal teams and external stakeholders to deliver enhancements and improvements.
- Support testing activities for new scheme configurations, pricing updates, and system changes.
- Help ensure the integrity and accuracy of pricing data and outputs.
- Contribute to the ongoing evolution of our pricing capabilities, including new technologies and automation tools.
Qualifications
We're looking for an analytical thinker who enjoys working with data and can interpret and communicate complex information clearly and confidently. You'll ideally bring:
- Advanced Microsoft Excel skills, including logical functions, formulas and data transformation techniques.
- Strong analytical and problem-solving skills.
- Experience working with pricing models, schemes, insurance products, or other highly analytical business processes.
- Strong communication skills and experience of working directly with clients to manage requests, answer queries, propose and explain solutions.
- Excellent attention to detail and a structured approach to tackling problems.
- Proactive approach to ensure clients' requests are responded to and completed as quickly as possible.
- The ability to manage multiple priorities and deliver high-quality outcomes.
Desirable Experience
While not essential, experience in any of the following areas would be highly advantageous:
- Knowledge of insurance pricing, underwriting, delegated authority schemes or related insurance disciplines.
- Python, SQL, R or similar programming and data analysis.
- Pricing platforms and rating engines, including experience supporting pricing technology implementations.
- Microsoft Copilot and AI-assisted productivity tools.
- Azure DevOps, Linear, or similar task and workflow management platforms.
- Software or user acceptance testing.
- Experience of working in a smaller team.
Data Analyst in Manchester employer: Verisk
Verisk is an exceptional employer, offering a dynamic work environment where innovation meets collaboration. As part of the Whitespace team in London, employees benefit from a culture that prioritises professional growth and development, alongside the opportunity to work with leading industry professionals on transformative projects. With a focus on employee well-being and a commitment to fostering long-term relationships, Verisk provides a rewarding career path for those looking to make a significant impact in the insurance technology space.
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We think this is how you could land Data Analyst in Manchester
✨Get Involved in Data Science Meetups
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We think you need these skills to ace Data Analyst in Manchester
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!
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Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Verisk. 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 Verisk
✨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!
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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 Verisk!
✨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.
