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- Tasks: Join us as a Data Modeller, analysing data and guiding implementation in financial services.
- Company: We are a leading employment agency focused on connecting talent with top-tier clients.
- Benefits: Enjoy flexible working options and access to corporate perks that enhance your career.
- Why this job: Make an impact in a regulated industry while developing your skills in SQL, Python, and SAS.
- Qualifications: Proficiency in programming languages and data modelling tools is essential; experience in financial services preferred.
- Other info: Your CV will be handled with care, ensuring your personal data is protected.
The predicted salary is between 28800 - 48000 £ per year.
Data Modeller with hands-on SAS data analysis/data modelling skills and a background in financial services or a highly regulated industry. Needs proficiency in programming languages (e.g. SQL, Python, R, SAS, or similar) and data modelling tools (e.g. ERStudio). Must have the ability to guide process experts to the right implementation approaches which align with industry standards and commonly accepted ITIL best practices.
Contact Detail:
Scope AT Limited Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Modeller/Data Analyst/Financial Services - SQL/Python/SAS
✨Tip Number 1
Familiarise yourself with the latest trends in data modelling and analysis within the financial services sector. This will not only help you understand the industry better but also allow you to speak confidently about relevant topics during interviews.
✨Tip Number 2
Brush up on your SQL, Python, and SAS skills by working on real-world projects or contributing to open-source initiatives. Demonstrating practical experience with these programming languages can set you apart from other candidates.
✨Tip Number 3
Network with professionals in the financial services and data analysis fields. Attend industry meetups, webinars, or conferences to make connections that could lead to job opportunities or valuable insights into the hiring process.
✨Tip Number 4
Prepare for potential technical interviews by practising common data modelling scenarios and problem-solving exercises. Being able to demonstrate your thought process and approach to data challenges can impress interviewers.
We think you need these skills to ace Data Modeller/Data Analyst/Financial Services - SQL/Python/SAS
Some tips for your application 🫡
Highlight Relevant Skills: Make sure to emphasise your proficiency in SQL, Python, SAS, and any other relevant programming languages. Mention specific projects or experiences where you utilised these skills, especially in financial services or regulated industries.
Showcase Data Modelling Experience: Detail your experience with data modelling tools like ERStudio. Provide examples of how you've guided process experts in implementing data solutions that align with industry standards and ITIL best practices.
Tailor Your CV: Customise your CV to reflect the job description closely. Use keywords from the job posting to ensure your application stands out and demonstrates that you meet the specific requirements of the role.
Craft a Strong Cover Letter: Write a compelling cover letter that explains why you're a great fit for the Data Modeller position. Discuss your passion for data analysis and how your background aligns with the company's goals in the financial services sector.
How to prepare for a job interview at Scope AT Limited
✨Showcase Your Technical Skills
Make sure to highlight your proficiency in SQL, Python, and SAS during the interview. Prepare examples of how you've used these programming languages in past projects, especially in data modelling or analysis within financial services.
✨Understand Industry Standards
Familiarise yourself with ITIL best practices and how they apply to data modelling in regulated industries. Be ready to discuss how you can guide process experts in implementing these standards effectively.
✨Prepare for Scenario-Based Questions
Expect scenario-based questions that assess your problem-solving skills. Think about challenges you've faced in previous roles and how you approached them, particularly in data analysis or modelling contexts.
✨Ask Insightful Questions
Prepare thoughtful questions about the company's data processes and tools. This shows your genuine interest in the role and helps you understand how you can contribute to their objectives.
