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For Companies At a Glance
- Tasks: Join our team to ensure data accuracy and integrity in finance.
- Company: Work with a global leader in the finance industry, known for innovation.
- Benefits: Enjoy remote work, world-class training, and potential for permanent roles.
- Why this job: Be part of a critical project that impacts the financial sector while developing your skills.
- Qualifications: Experience in data entry and quality assurance is essential; attention to detail is a must.
- Other info: Initial onsite training in London; flexible contract until Dec 2025 with extension possibilities.
The predicted salary is between 28800 - 43200 £ per year.
Job Description
Data Quality Assurance Analyst – Finance
Our client, a global leader in the finance industry, is seeking a meticulous and detail-oriented individual, with a demonstratable interest in finance to join their team on a temporary contract until end of Dec 2025 (high possibility of extension) with an immediate start date.
This is a remote role with initial onsite training (1-week) based in the City of London. This is an excellent opportunity for individuals with a keen eye for detail and a passion for maintaining data integrity to contribute to a critical project in the financial industry. Successful applicants will receive world-class training, work in a complex and exciting environment and will have the opportunity to apply for permanent roles within the business.
This position will be responsible for onboarding the Beneficial Ownership Registry data for Sweden. The successful candidate will play a crucial role in in onboarding and ensuring the accuracy of a new dataset.
The ideal applicant should have high level of attention to detail and strong experience in Data Entry & Quality Assurance.
Key Responsibilities:
- Entity Disambiguation: Accurately map holders to holder IDs, managing large amount of data (70,000 to 90,000 mappings), ensuring precision and consistency.
- Quality Assurance: Perform post-processing quality checks on all securities provided by the customer, ensuring data integrity and accuracy.
- Data Management: Assist in the management and organization of the dataset, ensuring all records are accurate and up-to-date.
Key Requirements:
- Previous experience in Data entry and Quality assurance is essential.
- Strong attention to detail, focus on accuracy and precision in data handling is a must.
- Ability to analyze data and identify discrepancies.
- Analytical skills to perform Quality Assurance.
- Ability to manage large volumes of data efficiently.
- Time management.
- Good Communication Skills (Verbal & Written).
- Experience or interest in finance in general.
If you are detail-oriented, experienced in data entry and quality assurance, and ready to contribute to a significant project, we encourage you to apply.
Unfortunately, we are only able to contact applicants who are successful to interview stage.
We are an equal opportunities employer and welcome applicants from all sections of the community, regardless of age, sex, gender (or gender identity), ethnicity, disability, sexual orientation, and transgender status.
Data Quality Assurance Analyst - Finance employer: Project Recruit
Contact Detail:
Project Recruit Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Quality Assurance Analyst - Finance
✨Tip Number 1
Familiarise yourself with the financial industry, especially concepts related to data integrity and quality assurance. This will not only help you understand the role better but also allow you to speak confidently about your interest in finance during any discussions.
✨Tip Number 2
Brush up on your data management skills, particularly in handling large datasets. Being able to demonstrate your ability to manage and analyse data efficiently will set you apart from other candidates.
✨Tip Number 3
Prepare for potential interview questions by practising how you would handle discrepancies in data. Think of examples from your past experience where you successfully identified and resolved data issues.
✨Tip Number 4
Network with professionals in the finance and data quality assurance fields. Engaging with others can provide insights into the role and may even lead to referrals or recommendations that could enhance your application.
We think you need these skills to ace Data Quality Assurance Analyst - Finance
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in data entry and quality assurance. Use specific examples that demonstrate your attention to detail and ability to manage large datasets.
Craft a Strong Cover Letter: In your cover letter, express your interest in finance and the role. Mention your analytical skills and how they relate to ensuring data integrity. Be sure to convey your enthusiasm for contributing to the project.
Highlight Relevant Skills: When filling out your application, emphasise your time management and communication skills. These are crucial for the role, so provide examples of how you've successfully used these skills in previous positions.
Proofread Your Application: Before submitting, carefully proofread your application materials. Check for any spelling or grammatical errors, as well as ensuring that all information is accurate and clearly presented.
How to prepare for a job interview at Project Recruit
✨Showcase Your Attention to Detail
As a Data Quality Assurance Analyst, your attention to detail is crucial. Be prepared to discuss specific examples from your past experiences where your meticulous nature helped identify discrepancies or improve data accuracy.
✨Demonstrate Your Analytical Skills
Highlight your ability to analyse data effectively. Prepare to explain how you approach data analysis and quality assurance, perhaps by discussing tools or methods you've used in previous roles.
✨Express Your Interest in Finance
Since this role is within the finance industry, make sure to convey your passion for finance. Share any relevant experiences or knowledge that demonstrate your interest and understanding of financial data management.
✨Prepare for Scenario-Based Questions
Expect scenario-based questions that assess your problem-solving skills in data management. Think about potential challenges you might face in the role and how you would address them, particularly regarding entity disambiguation and quality checks.
