At a Glance
- Tasks: Transform complex data into actionable insights and drive business decisions.
- Company: Join a dynamic team at a leading data analytics firm.
- Benefits: Flexible working, competitive salary, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on continuous learning and development.
- Why this job: Make a real impact by turning data into powerful stories for clients.
- Qualifications: Experience with Python, SQL, and data visualisation tools like Tableau.
The predicted salary is between 35000 - 45000 £ per year.
Location: Greater London, United Kingdom
Responsibilities:
- Turn large quantities of complex client data into insights which can be used to inform decision making and drive business benefit.
- Identify incomplete and diverse data sets, pinpoint data issues which may affect the accuracy and completeness of any analysis performed.
- Recognise the importance and value of understanding the data, validating the information provided and reconciling the datasets as part of the Data Analytics Cycle.
- Produce data visualisations, detailed reporting and analytics underpinned with clear business commentary.
- Collaborate closely with multi‑disciplined teams to deliver end‑to‑end client solutions in a timely manner.
- Balance the technical and analytical demands of the role.
- Be open‑minded and flexible with a thirst for knowledge and an appetite for continuous development.
Success Criteria:
- Clear, concise and insightful data analytics which enable clients to make sound business decisions based on fact.
- Ability to translate data analysis into targeted information which can be converted into actionable improvements, based on specific client/industry need.
- Continued improvement of Sagacity's Product Suite through the delivery of robust data insight.
- Accountability and ownership for client and internal deliverables.
- Contribute to a Data Analytics team by providing knowledge transfer support, peer‑to‑peer reviews, and mentoring to increase team skills and drive continuous learning.
Competencies & Behaviours:
- Proficiency in analytical programming languages such as Python and/or SQL.
- Understanding of relational databases and concepts for querying data.
- Proficiency in tools like Tableau and/or Power BI.
- Ability to balance time across multiple projects, planning ahead and working backwards from deadlines with all necessary steps (testing, QA) while proactively identifying risk and suggesting mitigation.
- Inquisitive, suggest "next steps" analysis and translate findings to actionable insight.
- Commercial experience within Telecoms, Banking or Utilities industries, or within a data‑related consultancy company would be beneficial.
- Able to travel throughout the United Kingdom.
- Can be based at a London office (minimum 2 days per week on site).
Data Analyst in London employer: Occupop
At Occupop, we pride ourselves on being an exceptional employer in the heart of Greater London, offering a dynamic work culture that fosters collaboration and innovation. Our commitment to employee growth is evident through continuous learning opportunities and mentorship within our Data Analytics team, ensuring that you can thrive both personally and professionally while contributing to impactful client solutions.
StudySmarter Expert Advice🤫
We think this is how you could land Data Analyst in London
✨Network Like a Pro
Get out there and connect with people in the industry! Attend meetups, webinars, or even casual coffee chats. We all know that sometimes it’s not just what you know, but who you know that can help you land that Data Analyst role.
✨Show Off Your Skills
Create a portfolio showcasing your data visualisations and analyses. Use platforms like GitHub to share your projects. We want to see your skills in action, so make sure you highlight your proficiency in Python, SQL, and tools like Tableau or Power BI!
✨Ace the Interview
Prepare for common interview questions related to data analysis and be ready to discuss your past experiences. We recommend practising with a friend or using mock interviews to boost your confidence. Remember, it’s all about showing how you can turn complex data into actionable insights!
✨Apply Through Our Website
Don’t forget to apply directly through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who take the initiative to reach out and show their interest in joining our team.
We think you need these skills to ace Data Analyst in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Data Analyst role. Highlight your experience with analytical programming languages like Python and SQL, and showcase any relevant projects or achievements that demonstrate your data analysis skills.
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about data analytics and how your skills align with the responsibilities outlined in the job description. Be sure to mention your experience with tools like Tableau or Power BI.
Showcase Your Problem-Solving Skills:In your application, emphasise your ability to identify data issues and provide actionable insights. Share examples of how you've tackled complex data challenges in the past, as this will resonate well with us at StudySmarter.
Apply Through Our Website:We encourage you to apply through our website for a smoother application process. This way, we can easily track your application and ensure it gets the attention it deserves. Good luck!
How to prepare for a job interview at Occupop
✨Know Your Data Tools
Make sure you brush up on your skills with analytical programming languages like Python and SQL, as well as data visualisation tools like Tableau or Power BI. Be ready to discuss how you've used these tools in past projects, as this will show your practical experience and understanding of the role.
✨Understand the Business Context
Before the interview, research the company and its industry. Understand how data analytics can drive decision-making in sectors like Telecoms, Banking, or Utilities. This knowledge will help you tailor your answers and demonstrate that you can translate data insights into actionable business improvements.
✨Prepare for Scenario Questions
Expect questions that ask you to solve hypothetical data issues or analyse a dataset. Practice explaining your thought process clearly and concisely. Use examples from your past experiences to illustrate how you’ve tackled similar challenges, focusing on your analytical approach and problem-solving skills.
✨Show Your Collaborative Spirit
Since the role involves working closely with multi-disciplined teams, be prepared to discuss your experience in collaboration. Share examples of how you've contributed to team projects, mentored peers, or facilitated knowledge transfer. Highlighting your teamwork skills will show that you're a good fit for their culture.
