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Stockholm, Sverige
Onsite
Neko is redefining what prevention means, from treating illness when it arrives, to sustaining health before it's ever at risk. Our mission: make data-driven, preventative care accessible to more people, before symptoms appear.
In a single, non-invasive visit under an hour, proprietary technology and direct clinical care combine to deliver personalised, actionable insights. It's a team that thinks in 10x, not 10%. Every role here plays a part in building a world where prevention is the norm, and where your work genuinely helps people live longer, healthier lives.
At Neko Health, our mission is to deliver proactive healthcare for all, empowering members to take control of their health through cutting-edge technology and compassionate care. As a Data Annotator, you will support our AI and Machine Learning teams by reviewing and accurately annotating health-related data according to defined guidelines. Your work will help create high-quality datasets that enable the development and improvement of our preventive healthcare technology. This role requires a high level of integrity, strong attention to detail, consistency, and the ability to work efficiently with large volumes of data.
Label and quality-check images/audio using our annotation tools.
Follow clear guidelines and examples to label consistently and accurately.
Flag unclear cases or data issues, and escalate to the team when needed.
Help improve our labelling instructions by reporting edge cases and tool friction.
Comfortable working on a computer all day and a fast learner with new software.
Experience to data analysis, data science, medical imaging or data annotation.
High attention to detail and consistency; you enjoy structured tasks.
Reliable, able to hit daily throughput targets without sacrificing quality.
Professional with sensitive data, with a privacy-first mindset.
Eligible to work in Sweden.
Experience with annotation tools, QA/review work, data analysis, or repetitive production workflows.
Interest in health/tech, data science, machine learning, or AI (no medical background required).
