At a Glance
- Tasks: Ensure accurate pension data by cross-referencing and matching information.
- Company: Join a dedicated team in the Local Government Pension Scheme.
- Benefits: Gain valuable experience, develop IT skills, and work in a supportive environment.
- Other info: Opportunity to learn about pension regulations and grow your career.
- Why this job: Make a real difference in people's lives by ensuring their pension benefits are accurate.
- Qualifications: GCSEs in English, Maths, and ICT; strong IT and communication skills required.
The predicted salary is between 24000 - 28000 £ per year.
About the role:
To undertake administration tasks in order to maintain accurate member data to calculate and pay pension benefits to a specific category of membership. Works under general instruction and guidance.
About you:
- Experience of the use of IT packages e.g. MS Office, MS365 with strong IT skills.
- Familiarity with Excel is crucial.
- Good oral and written communication skills.
- Understanding and awareness of quality assurance skills.
- A basic working knowledge of LGPS.
- Educated to at least GCSE (or equivalent) in English, Maths and ICT.
- Ability to work well in a team as well as using your own initiative.
What you will do:
As a Data Quality Assistant within the Pensions service area, you will play a crucial role in ensuring the accuracy and integrity of pension data. Your primary responsibility will be to cross-reference and match employer and pension-held data, ensuring all information is correct and up to date. This role involves manipulating data between different systems, contributing to the smooth operation of our pension services.
To maintain working knowledge of relevant Pension Scheme Regulations, procedures and other statutory arrangements and to their revisions as necessary.
Your responsibilities will be:
To assist with the pensions administration of the Local Government Pension Scheme and, in accordance with the appropriate regulations, including checking applications for.
Data Quality Assistant in London employer: JOB SWITCH LTD
As a Data Quality Assistant, you will join a supportive and collaborative work environment dedicated to maintaining the integrity of pension data. Our company values employee growth, offering training and development opportunities to enhance your skills in data management and quality assurance. Located in a vibrant community, we provide a fulfilling career path with competitive benefits, ensuring that our team members feel valued and engaged in their roles.
StudySmarter Expert Advice🤫
We think this is how you could land Data Quality Assistant in London
✨Embrace Online Competitions
Get involved in online data science competitions like Kaggle or DrivenData. These platforms not only let you showcase your skills but also help you build a portfolio that stands out to hiring companies like JOB SWITCH LTD when you're aiming for that entry-level role.
✨Join Data Science Meetups
Look for local data science meetups or workshops happening in your area. These are perfect for connecting with industry professionals and fellow newbies, giving us the chance to learn the ropes and get our foot in the door at companies like JOB SWITCH LTD.
✨Networking Through University Career Services
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✨Spotlight Your Skills Online
Create a strong online presence by sharing your projects and insights on platforms like GitHub or LinkedIn. Make sure to apply directly through JOB SWITCH LTD’s career page, where your unique skills can shine in their entry-level data science openings!
We think you need these skills to ace Data Quality Assistant in London
Some tips for your application 🫡
Show Off Your Data Skills:As you're aiming for an entry-level data science role at JOB SWITCH LTD, don't forget to highlight your proficiency in programming languages like Python or R. Dive into your CV and mention any relevant projects or coursework that demonstrate your data analysis skills or machine learning knowledge.
Include Relevant Projects:If you've done any data-related projects, whether in your studies or during a personal quest, showcase them in a portfolio. This gives us a tangible sense of your capabilities and shows your hands-on experience with data manipulation, visualisation, or model building.
Tailor Your Cover Letter:When crafting your cover letter, make sure to express your enthusiasm for data science and how this role at JOB SWITCH LTD aligns with your career goals. Consider sharing why you’re drawn to data-driven decision-making and how you see yourself growing in this field.
Show Your Curiosity:In the data science world, curiosity is key! Mention any online courses or certifications you've pursued that complement your studies. This could be anything from a statistics certification to a data visualisation workshop. It shows us you're serious about learning and growing in this field.
How to prepare for a job interview at JOB SWITCH LTD
✨Brush Up on Your Statistics
For a data science role, the interview may involve some statistical questions or problems. Make sure you're comfortable with concepts like probability, distributions, and hypothesis testing. This will not only help you answer questions but also show your analytical thinking.
✨Get Hands-On with Tools
Familiarise yourself with popular data science tools like Python, R, and SQL. If you're asked about specific projects, be ready to discuss the tools you used and how they contributed to your analysis. Showing that you not only know the theory but can apply it is essential!
✨Showcase Relevant Projects
As an entry-level candidate, your portfolio is crucial. Bring along examples of data projects you've worked on, whether during your studies or personal projects. Discuss the challenges you faced and how you overcame them, highlighting your problem-solving skills.
✨Prepare for Case Studies
Entry-level interviews in data science often include case studies where you'll have to analyse a dataset or solve a problem on the spot. Try out some practice case studies beforehand, so you're not caught off guard. It's all about displaying your thought process and how you tackle data-driven challenges!
