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For Companies At a Glance
- Tasks: Analyse data, create models, and present insights using advanced tools.
- Company: Join a dynamic team in a leading tech environment focused on innovation.
- Benefits: Enjoy competitive pay, flexible work locations, and opportunities for growth.
- Why this job: Make an impact with your skills while working in a collaborative culture.
- Qualifications: Expertise in SQL, data visualisation, and recent experience in data cleansing required.
- Other info: This role offers a chance to work with AI/ML toolsets for cutting-edge analysis.
Role: Data Analyst Location: Choice of London/Bristol/Leeds/Manchester Duration: 3 Months (Expected to be up to 18 months in total) Day rate: £450 – £495 inside IR35 Required skills & experience: Expert Microsoft SQL Server database analyst Experienced data modelling skills Data dictionary creation and support M365 Graph/PowerShell skills to extract SharePoint, groups and membership data Demonstrable experience of R/Python Expert Data Visualisation skills Statistical Analysis knowledge Excellent Communication and writing skills, will need to present data Recent (last 24 months) data cleansing experience Source to target mapping and Extract Transform and Load/Extract Load and Transform (Last 24 months) Use of AI/ML toolsets for data analysis and automation
Contact Detail:
Experis Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Analyst
✨Tip Number 1
Familiarise yourself with the latest trends in data analysis, especially focusing on AI and machine learning toolsets. This will not only enhance your skills but also show us that you're proactive and up-to-date with industry standards.
✨Tip Number 2
Network with current or former Data Analysts at StudySmarter or similar companies. Engaging in conversations can provide you with insights into our work culture and expectations, which can be invaluable during interviews.
✨Tip Number 3
Prepare to discuss specific projects where you've used SQL Server and data visualisation tools. Being able to articulate your hands-on experience will demonstrate your expertise and make you stand out.
✨Tip Number 4
Brush up on your communication skills, as presenting data effectively is crucial for this role. Practising how to convey complex information clearly can set you apart from other candidates.
We think you need these skills to ace Data Analyst
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Microsoft SQL Server, data modelling, and any relevant tools like R or Python. Use specific examples to demonstrate your skills in data visualisation and statistical analysis.
Craft a Strong Cover Letter: In your cover letter, explain why you're interested in the Data Analyst role and how your recent experience aligns with the job requirements. Mention your familiarity with AI/ML toolsets and your ability to communicate complex data insights effectively.
Showcase Relevant Projects: If you have worked on projects involving data cleansing, source to target mapping, or ETL processes, be sure to include these in your application. Highlight any specific achievements or outcomes from these projects.
Proofread Your Application: Before submitting, carefully proofread your application for any spelling or grammatical errors. A well-written application reflects your communication skills, which are crucial for this role.
How to prepare for a job interview at Experis
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Microsoft SQL Server, R/Python, and data visualisation tools. Bring examples of past projects where you successfully used these skills, as this will demonstrate your expertise and ability to handle the role's requirements.
✨Prepare for Data Modelling Questions
Since data modelling is a key part of the job, brush up on your knowledge and be ready to explain your approach to creating data models. You might be asked to walk through a specific example, so having a clear process in mind will help you stand out.
✨Communicate Clearly
Excellent communication skills are essential for this role. Practice explaining complex data concepts in simple terms, as you may need to present your findings to non-technical stakeholders. This will show that you can bridge the gap between data and decision-making.
✨Demonstrate Recent Experience
Highlight your recent experience with data cleansing and ETL processes. Be ready to discuss specific challenges you faced and how you overcame them, as well as any AI/ML toolsets you've used for data analysis. This will show that you're up-to-date with industry practices.
