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Information Technology
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Data Scientist

Neko Health
Germany
Verified OpportunityChecked by PathwayAI staff.

Role Summary

Join Neko Health as a Data Scientist in London, focusing on data-driven preventive health solutions. Opportunity available for international applicants.

About the Organisation

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.

Neko Health is a Swedish healthcare technology company co-founded in 2018 by Hjalmar Nilsonne and Daniel Ek. Neko's vision is to shift healthcare from reactive treatment toward preventative health and early detection. This requires completely reimagining the patient's experience and incorporating the latest advances in sensors and AI. Neko Health has developed a new medical scanning technology concept to make it possible to do broad and non-invasive health data collection that is convenient and affordable for the public. The company is based in Stockholm, offering the Neko Body Scan experience at locations in Stockholm, London and Manchester, with over 500 employees.

A Data Scientist at Neko Health develops and implements data solutions that drive insights from sensor and healthcare data, enabling clinical decision support, and supporting innovations. This role partners with clinical researchers, engineers, and other teams to enhance products through data-driven insights.

The engineering team is divided into smaller cross functional project teams that each focus on a specific goal or target, where some groups are long-lived, and some are short-lived, depending on how big the goal or deliverable is. We strive to create groups which are cross-functional and able to complete their goals without dependence on other teams, even though this is of course not always possible.

Groups track goals on a yearly and quarterly basis with goal follow-up across the entire engineering organization on a bi-weekly basis. Most groups do internal planning on a bi-weekly basis, but in the end it's up to the group to decide how they want to work.

We have, however, mandated that all groups must present their progress or failures or hacks at our bi-weekly engineering demo, a fun meeting/presentation where we talk about everything from short-circuiting power-modules, how hard it is to calibrate cameras or align polygons in space, to neat new command line tools for operations, a new auth mechanism in the backend, a cool new way to visualize health data or a new feature which helps our doctors be more productive.

We have a flexible workplace that focuses on work/life balance, and we strongly believe in our mission but do not think that achieving it requires sacrificing everything else.

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Key Responsibilities

  • Data Modeling and Analysis: Develop algorithms, statistical models and machine learning models to address targeted challenges using sensor and healthcare data. Develop performance evaluation and implement performance monitoring of data products to ensure that the intended value is delivered.
  • Data Management: Prepare, clean, and integrate datasets from various sources, ensuring data quality and accuracy. Collaborate with Data Engineers to build and maintain scalable data pipelines for efficient analysis.
  • Support for Clinical Studies: Collaborate with clinical teams to define targeted clinical hypotheses, study variables and collection methods for clinical studies. Perform exploratory analyses and provide data insights to refine study designs.
  • Research and Innovation: Stay up-to-date on data science advances to continuously improve model accuracy, efficiency, and clinical relevance. Develop proofs-of-concept of new medical devices and methods. Support patent development.
  • Maintenance, scaling, and common tooling: Improve robustness of products, streamlining of processes and increasing efficiency of data science development by applying good software engineering practices.

Minimum Requirements

  • MSc or PhD degree in a quantitative field for example Computer Science, Machine Learning or Physics.
  • Expertise within data science, algorithm development, and statistics.
  • Strong analytical abilities, collaborative mindset, and solid software engineering skills.
  • A strong proficiency in designing and implementing machine learning algorithms.

Eligibility Criteria

Eligible candidates include those with an MSc or PhD in a quantitative field and strong analytical abilities.

Exp. LevelNot specified
EducationNot specified

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Published On
August 22, 2026
Application Deadline
Ongoing / No specific deadline
Location
London
Employment Type
Full Time • On-site
Source
Arbeitnow
Last verified: August 24, 2026
Degree Level
Master's
Visa Sponsorship
Visa Sponsorship Likely
Africa Eligibility
International — African Eligibility Unclear
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