Turning data into something useful takes more than tools. It takes curiosity, precision and the ability to ask the right questions.
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About the position
A junior data analyst at Synthesis supports the development of data, automation, and AI-enabled workflows across client and internal projects. They work on clearly scoped analytical and technical tasks, helping clean, collect, structure, analyze, and prepare data for practical business use.
We are looking for someone with a good foundation in Python, strong attention to detail, and curiosity about AI tools, automation, data analysis, and technical problem-solving. This role is best suited for someone early in their data career who wants to grow by working across varied projects, industries, and data challenges.
The challenges you’ll take on:
- Support data and AI-based projects by completing clearly scoped technical and analytical tasks
- Clean, structure, transform, and analyze data using Python and agreed tools or workflows
- Help collect data from different sources, including scraping and structured data collection tasks
- Prepare datasets, tables, charts, summaries, and first-draft analytical outputs
- Use existing scripts, templates, and workflows correctly, improving them where useful
- Check output quality before handover and clearly document analysis logic
- Flag blockers, data quality issues, or unclear requirements early
- Keep own work organized and visible to the project lead
- Contribute to internal experimentation with AI tools, automation workflows, and analytical methods
- Collaborate with project leads and cross-functional teams across research, strategy, data, and design projects
We expect you to:
- Have basic to good working knowledge of Python for data cleaning, transformation, analysis, or visualization
- Be interested in data analysis, automation, AI tools, and practical technical problem-solving
- Be able to work with structured data such as spreadsheets, CSV files, databases, or survey data
- Have some experience with scraping, data collection, or working with multiple data sources
- Be familiar with AI tools and curiosity about how they can support research, analysis, and workflow automation
- Have a basic understanding of Git or willingness to learn version control and collaborative development workflows
- Write code that is understandable, organized, and reliable for the intended task
- Pay attention to detail and habit of checking your work before handover
- Communicate clearly and explain what was done, what the data shows and where there are limitations
- Be willing to learn from feedback and apply it in the next version of your work
Gross salary: 1300 - 1700 Eur
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