At a Glance
- Tasks: Transform complex data into engaging stories and user-friendly dashboards.
- Company: Join Infogr8, a leader in data storytelling and visual design.
- Benefits: Flexible work environment, creative freedom, and opportunities for professional growth.
- Other info: Embrace innovative AI tools to enhance your creative process.
- Why this job: Make a real difference by turning data into impactful narratives across various sectors.
- Qualifications: Experience in data visualisation, storytelling, and collaboration with diverse teams.
The predicted salary is between 50000 - 65000 £ per year.
Infogr8 is seeking a Data Experience Lead to turn complex evidence into clear data stories, dashboards and digital experiences people actually use.
This hands-on role blends data, story, and design, working across education, health, and public-interest projects.
You’ll guide how clients understand information, shape editorial approaches, and collaborate with designers, developers and analysts to deliver coherent, high-quality outputs while embracing AI tools to speed up research and prototyping.
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Lead, Data Experience & Visual Storytelling employer: Data Visualization Society
Infogr8 is an exceptional employer that fosters a collaborative and innovative work culture, where creativity meets data-driven insights. As a Director of Client Partnerships, you will have the opportunity to build meaningful relationships with high-profile clients while contributing to impactful projects that shape the future of data visualisation. With a clear pathway to senior leadership roles and a commitment to employee growth, Infogr8 offers a unique environment for those passionate about transforming complex information into engaging narratives.
Contact Details:
Data Visualization Society Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Lead, Data Experience & Visual Storytelling
✨Get Involved in Data Science Meetups
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We think you need these skills to ace Lead, Data Experience & Visual Storytelling
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!
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Craft a Tailored Cover Letter:For a full-time role at Data Visualization Society, 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 Data Visualization Society. 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 Data Visualization Society
✨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!
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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
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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.