Data Quality & Asset Data Coordinator | Flexible Hours in Liverpool

Data Quality & Asset Data Coordinator | Flexible Hours in Liverpool

Liverpool Full-Time 24750 - 30250 £ / year (est.) Home office (partial)
Riverside

At a Glance

  • Tasks: Coordinate asset data projects and improve data quality across built assets.
  • Company: Riverside, a forward-thinking organisation in Liverpool.
  • Benefits: Flexible working hours and a strong pension package.
  • Other info: Join a supportive team with opportunities for growth.
  • Why this job: Make a real difference by ensuring high-quality data standards.
  • Qualifications: Analytical skills and attention to detail required.

The predicted salary is between 24750 - 30250 £ per year.

Riverside is hiring a Data Quality Officer to support the Planning & Performance Team in Liverpool.

The role focuses on coordinating asset data projects, maintaining plans and logs, and delivering data quality improvements across built assets.

The successful candidate will analyse information from multiple sources, prepare summaries, and ensure governance and documentation standards are followed.

Riverside offers flexible working and a strong pension package.

#J-18808-Ljbffr

Data Quality & Asset Data Coordinator | Flexible Hours in Liverpool employer: Riverside

As a People Service Delivery Manager at our Liverpool location, you will join a dynamic and supportive work culture that prioritises employee growth and development. We offer competitive pay, generous pension schemes, and flexible working options, ensuring a healthy work-life balance while investing in your personal and professional development. Our commitment to diversity and inclusion makes us an excellent employer, providing guaranteed interview opportunities for candidates from diverse backgrounds.

Riverside

Contact Details:

Riverside Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Data Quality & Asset Data Coordinator | Flexible Hours in Liverpool

Get Involved in Data Science Meetups

Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Riverside!

Show Off Your Projects

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 Data Quality & Asset Data Coordinator | Flexible Hours at Riverside.

Leverage Professional Networks

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 Riverside.

Apply Directly through Our Website

When you find a suitable opening like Data Quality & Asset Data Coordinator | Flexible Hours at Riverside, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!

We think you need these skills to ace Data Quality & Asset Data Coordinator | Flexible Hours in Liverpool

Communication Skills
Problem-Solving Skills
Attention to Detail
SQL
Python
Data Governance
Automation

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 Riverside, 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 Riverside. 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 Riverside

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 Riverside!

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.