At a Glance
- Tasks: Analyse HR data and create insightful reports to support decision-making.
- Company: Join a dynamic HR team with a focus on data-driven insights.
- Benefits: Flexible working hours, competitive pay, and mostly remote work.
- Other info: Enjoy a flexible schedule with opportunities for in-office collaboration.
- Why this job: Make a real impact by transforming data into actionable insights.
- Qualifications: Strong Excel skills and analytical mindset; HR experience is a plus.
The predicted salary is between 20 - 20 £ per hour.
HR Data Analyst (Part-Time Contract) – Flexible (UK) – commutable to Preston or Portsmouth
6 months | 20 hours per week | £20 per hour PAYE | Inside IR35
Mostly remote (1–2 days in office per month)
The Role
We’re looking for a skilled HR Data Analyst to support our HR team with data reporting, analysis, and insights. You’ll work with multiple HR systems to produce clear, meaningful data that supports decision-making.
Key Responsibilities
- Analyse and report on HR data (e.g. headcount, attrition, absence)
- Build and maintain dashboards and reports
- Combine data from multiple systems into clear insights
- Identify trends and provide actionable recommendations
- Support HR teams with data-driven decision-making
- Improve data quality and reporting processes
About You
- Strong Excel and analytical skills (essential)
- Able to interpret data and explain trends clearly
- Experience in data analysis (HR experience beneficial but not required)
- Confident communicating insights to non-technical stakeholders
Additional Info
- Flexible working pattern (3 days or spread across 4–5 days)
- Occasional in-office meetings required
- BPSS clearance required
Data Analyst SQL Python Tableau in Preston employer: Outsource UK
Join a dynamic and supportive team as a Data Analyst, where flexibility and work-life balance are prioritised. With the opportunity to work mostly remotely and only occasional in-office meetings, you can enjoy a fulfilling career while contributing to meaningful HR insights. Our culture fosters professional growth, encouraging you to develop your analytical skills in a collaborative environment that values data-driven decision-making.
StudySmarter Expert Advice🤫
We think this is how you could land Data Analyst SQL Python Tableau in Preston
✨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 Outsource UK.
✨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 Outsource UK 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 Data Analyst SQL Python Tableau in Preston
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 Outsource UK 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 Outsource UK
✨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 Outsource UK.
✨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 Outsource UK.
✨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 Outsource UK, 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 Outsource UK 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.
