Part-Time Data Insights & BI Analyst — Bristol

Part-Time Data Insights & BI Analyst — Bristol

Part-Time 31500 - 38500 £ / year (est.) No working from home possible
Alexander Mae (Bristol) Ltd

At a Glance

  • Tasks: Analyse data and produce reports to support business operations and strategy.
  • Company: Join a dynamic team at Alexander Mae in vibrant Bristol.
  • Benefits: Part-time role with competitive salary and flexible hours.
  • Why this job: Make an impact by driving insights that shape business decisions.
  • Qualifications: Experience in data analysis and reporting is preferred.

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

Alexander Mae (Bristol) Ltd is hiring a Data Insights & Business Intelligence Analyst based in Bristol, Avon, South West, UK.

This is a Part time opportunity (£28,000).

On behalf of our client, we are seeking a Data Insights & Business Intelligence Analyst to join their team in central Bristol.

This role supports SLS operations by producing and analysing reporting, ensuring performance aligns with strategy and regulatory requirements.

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Part-Time Data Insights & BI Analyst — Bristol employer: Alexander Mae (Bristol) Ltd

At Alexander Mae (Bristol) Ltd, we pride ourselves on being an excellent employer that fosters a supportive and collaborative work culture. Our commitment to employee growth is evident through ongoing training and development opportunities, ensuring that our team members thrive in their roles. Located in the vibrant city of Bristol, we offer a dynamic environment where your contributions are valued, making this a truly rewarding place to advance your career in financial services.

Alexander Mae (Bristol) Ltd

Contact Details:

Alexander Mae (Bristol) Ltd Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Part-Time Data Insights & BI Analyst — Bristol

Get Involved in Data Challenges

Participate in data challenges like Kaggle competitions or DrivenData to showcase your skills and network with other data enthusiasts. Not only will you build your portfolio, but you can also catch the eye of potential employers like Alexander Mae (Bristol) Ltd.

Connect with Local Data Communities

Join local data science meetups or online communities like Data Science Society to engage with professionals in the field. These platforms are great for networking, discovering job opportunities, and keeping your fingers on the pulse of industry trends.

Leverage Your University’s Resources

If you're still in university, make full use of your career services. They might have part-time roles tailored for students like you, and often have direct connections with companies looking to hire talented interns in data science roles.

Apply Directly Through Our Website

Don’t forget to check out our jobs at Alexander Mae (Bristol) Ltd and apply through our website! It’s the best way to ensure your application gets seen. Plus, we love hearing from passionate individuals like us who are eager to make an impact in the data science world.

We think you need these skills to ace Part-Time Data Insights & BI Analyst — Bristol

Data Analysis
Business Intelligence
Reporting Skills
Performance Analysis
Regulatory Compliance
Strategic Alignment
Analytical Skills

Some tips for your application 🫡

Show Your Data Skills:In your CV, make sure to highlight your proficiency with key data analysis tools and programming languages like Python, R, or SQL. We want to see that you've got hands-on experience with data manipulation and visualisation, so if you've worked on any relevant projects or coursework, include those details to really showcase your skills!

Tailor Your Projects Towards Data Science:When it comes to your portfolio, focus on showcasing projects that highlight your data-science abilities. Include analyses, dashboards, or any predictive models you've built. If you've contributed to Kaggle competitions or have a GitHub repository with data projects, make sure to link those—these demonstrate your practical experience and problem-solving abilities.

Express Your Motivation in the Cover Letter:Since this is a part-time role, we want to know why you're particularly interested in juggling this with your other commitments. Use your cover letter to express your passion for data science and how this role at Alexander Mae (Bristol) Ltd aligns with your career aspirations. Show us you're excited about learning and growing with us!

Keep It Concise Yet Informative:Part-time positions often receive many applications, so keep your documents clear and to the point! Aim for a concise CV detailing your relevant experiences without unnecessary fluff. Be sure to include your availability in your cover letter as well—that helps us in the decision-making process!

How to prepare for a job interview at Alexander Mae (Bristol) Ltd

Brush Up on Your Stats!

Given you're eyeing a part-time role in data science, make sure you’re on top of your statistical methods and data analysis techniques. Expect questions around regression, hypothesis testing, and maybe even some statistical programming languages like R or Python during the interview with Alexander Mae (Bristol) Ltd.

Show Off Your Projects!

It's crucial to have a portfolio that showcases your data science projects. Highlight your part-time work with specific data sets, models you've built, or analyses you've conducted. Having tangible examples will demonstrate your hands-on experience and problem-solving skills to Alexander Mae (Bristol) Ltd.

Familiarise Yourself with Tools of the Trade

Make sure you’re well-versed in data science tools like Jupyter Notebook, Tableau, or SQL. You might get technical questions or even a practical test at Alexander Mae (Bristol) Ltd, so having a comfort level with these tools will definitely be an advantage.

Be Ready to Discuss Real-World Applications

Since this is a part-time role, employers at Alexander Mae (Bristol) Ltd will likely appreciate your understanding of how data science can address actual business problems. Be prepared to discuss any relevant case studies or how you would approach specific challenges in real scenarios.