Power BI Data Analyst β€” Self-Service Insights in Paisley

Power BI Data Analyst β€” Self-Service Insights in Paisley

Paisley Full-Time 31500 - 38500 Β£ / year (est.) No working from home possible
Kibble

At a Glance

  • Tasks: Design and build self-service reporting and automated insights using Power BI.
  • Company: Join Kibble, a forward-thinking charity focused on digital transformation.
  • Benefits: Enjoy a competitive salary, flexible working options, and opportunities for professional growth.
  • Other info: Collaborative environment with a focus on innovation and impact.
  • Why this job: Make a real difference by enabling data-informed decisions across the organisation.
  • Qualifications: Experience with Power BI and a passion for data analysis.

The predicted salary is between 31500 - 38500 Β£ per year.

Kibble is seeking a Data Analyst to accelerate our digital-first reporting across the organisation.

You will partner with all departments to design, build and sustain self-service reporting and automated insight, via Power BI connected to Dynamics 365, F&O, BC, and the broader Microsoft 365 suite.

The role is based at our Paisley Campus and involves collaborating with multiple teams to deliver reliable dashboards, govern data, and enable data-informed decisions across the charity.

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Power BI Data Analyst β€” Self-Service Insights in Paisley employer: Kibble

Kibble in Paisley is an exceptional employer dedicated to fostering a supportive and collaborative work environment for healthcare professionals. With a strong focus on employee growth, we offer ongoing training and development opportunities, allowing you to enhance your skills while making a meaningful difference in the lives of young people. Our commitment to health and wellbeing initiatives not only benefits our clients but also creates a fulfilling workplace culture that values teamwork and compassion.

Kibble

Contact Details:

Kibble Recruitment Team

StudySmarter Expert Advice🀫

We think this is how you could land Power BI Data Analyst β€” Self-Service Insights in Paisley

✨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 Kibble!

✨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 Power BI Data Analyst β€” Self-Service Insights at Kibble.

✨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 Kibble.

✨Apply Directly through Our Website

When you find a suitable opening like Power BI Data Analyst β€” Self-Service Insights at Kibble, 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 Power BI Data Analyst β€” Self-Service Insights in Paisley

Power BI
Data Analysis
Dynamics 365
Microsoft 365
Dashboard Design
Data Governance
Collaboration Skills

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 Kibble, 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 Kibble. 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 Kibble

✨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 Kibble!

✨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.