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- Tasks: Enhance data quality standards and conduct root cause analysis in the insurance sector.
- Company: Leading data services firm in the UK with a focus on innovation.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Why this job: Shape the future of data quality in the insurance industry and make a real impact.
- Qualifications: 5+ years in data quality or governance, strong SQL and Python skills.
- Other info: Collaborative environment with a focus on career advancement.
The predicted salary is between 43200 - 72000 £ per year.
A leading data services firm in the UK is seeking a Senior Data Quality Analyst to enhance data quality across the insurance sector. The role involves shaping and governing data quality standards, conducting root cause analysis, and collaborating with various teams to ensure data alignment with business objectives.
The ideal candidate will have over 5 years of experience in data quality or governance, with a strong focus on the insurance domain and proficiency in SQL and Python.
Senior Data Quality Strategist – Insurance Analytics employer: Oliver James
Contact Detail:
Oliver James Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Quality Strategist – Insurance Analytics
✨Tip Number 1
Network like a pro! Reach out to folks in the insurance analytics space on LinkedIn or at industry events. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Prepare a portfolio or case studies showcasing your data quality projects, especially those related to insurance. This will give you an edge during interviews.
✨Tip Number 3
Practice makes perfect! Get comfortable with common interview questions for data quality roles. We recommend doing mock interviews with friends or using online platforms to boost your confidence.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Senior Data Quality Strategist – Insurance Analytics
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Senior Data Quality Strategist role. Highlight your experience in data quality and governance, especially within the insurance sector. We want to see how your skills align with our needs!
Showcase Your Skills: Don’t forget to showcase your proficiency in SQL and Python! Include specific examples of how you've used these skills in past roles. This will help us see your technical capabilities right off the bat.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about data quality in the insurance industry and how you can contribute to our team. We love seeing genuine enthusiasm!
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It helps us keep everything organised and ensures your application gets the attention it deserves. Let’s make it happen!
How to prepare for a job interview at Oliver James
✨Know Your Data Quality Standards
Make sure you’re well-versed in data quality standards specific to the insurance sector. Brush up on industry best practices and be ready to discuss how you've implemented these in your previous roles.
✨Showcase Your Technical Skills
Since proficiency in SQL and Python is crucial, prepare to demonstrate your skills. You might be asked to solve a problem or analyse a dataset during the interview, so practice coding challenges beforehand.
✨Prepare for Root Cause Analysis Questions
Expect questions that assess your ability to conduct root cause analysis. Think of examples from your past experience where you identified issues and implemented solutions, and be ready to explain your thought process.
✨Collaboration is Key
This role involves working with various teams, so be prepared to discuss your experience in cross-functional collaboration. Share specific examples of how you’ve worked with different stakeholders to align data quality with business objectives.
