Remote-First Data Scientist for Health Sensors & AI

Neko Health AB; Greater London; Remote; GBP 70,000 - 110,000; Full time

Benefits offered by this job

Remote First

Job summary

Neko Health AB is seeking a Data Scientist to transform sensor and healthcare data into actionable clinical insights and support data-driven decisions across products.

You will collaborate with clinical researchers, engineers, and product teams in a Remote First environment to enhance models, experiments, and scalable data pipelines while ensuring scientific rigor and regulatory alignment.

Qualifications

• MSc or PhD in a quantitative field such as Computer Science, Machine Learning or Physics.
• Expertise in 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.

Responsibilities

• Data Modeling and Analysis: Develop algorithms, statistical models and ML models to address challenges using sensor/healthcare data; monitor data products.
• Data Management: Clean and integrate datasets; collaborate on scalable data pipelines.
• Support for Clinical Studies: Collaborate with clinical teams to define hypotheses and study variables.
• Research and Innovation: Stay updated on data science advances; prototype new methods and support patent development.
• Maintenance, scaling, and tooling: Improve robustness and efficiency of data science processes.

Skills

Data science

Algorithm development

Statistics

Software engineering

Machine learning

Education

MSc or PhD in quantitative field

Tools

Python

C++

Typescript

C#

Azure Cosmos DB

ASP.NET Core

Job description

Neko Health AB is seeking a Data Scientist to transform sensor and healthcare data into actionable clinical insights and support data-driven decisions across products.

You will collaborate with clinical researchers, engineers, and product teams in a Remote First environment to enhance models, experiments, and scalable data pipelines while ensuring scientific rigor and regulatory alignment.