At a Glance
- Tasks: Ensure data quality and accuracy across insurance systems while collaborating with various teams.
- Company: AXIS Capital, a leader in modernising data for the insurance industry.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Exciting role with strong stakeholder engagement and career advancement potential.
- Why this job: Join a dynamic team to make a real impact on data quality in insurance.
- Qualifications: Proficiency in SQL, Excel, and data visualisation tools like Power BI or Tableau.
The predicted salary is between 50000 - 60000 £ per year.
AXIS Capital is seeking a Data Quality Business Partner to help modernise our data estate. You will partner with underwriting, claims and finance to ensure data quality, accuracy and usability across policy, claims and pricing systems.
You will develop rules, monitor quality, and drive improvements in collaboration with IT and governance teams. The role requires SQL, Excel and data-visualisation tool proficiency (Power BI, Tableau) and a strong stakeholder-management mindset.
#J-18808-LjbffrHybrid Data Quality Partner for Insurance employer: AXIS (AXIS Capital)
AXIS Capital is an exceptional employer, offering a dynamic work environment in London where actuaries can thrive as strategic partners to senior leadership. With a strong focus on employee growth and development, AXIS provides a competitive benefits package and fosters a collaborative culture that encourages innovative thinking and impactful contributions to business planning.
StudySmarter Expert Advice🤫
We think this is how you could land Hybrid Data Quality Partner for Insurance
✨Get Involved in Data Science Meetups
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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 Hybrid Data Quality Partner for Insurance at AXIS (AXIS Capital).
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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 AXIS (AXIS Capital).
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We think you need these skills to ace Hybrid Data Quality Partner for Insurance
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 AXIS (AXIS Capital), 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 AXIS (AXIS Capital). 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 AXIS (AXIS Capital)
✨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 AXIS (AXIS Capital)!
✨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.
