Neko Health is a Swedish health-tech company co-founded in 2018 by Hjalmar Nilsonne and Daniel Ek. Neko's vision is to create a healthcare system that can help people stay healthy through preventive…
Neko Health is a Swedish health-tech company co-founded in 2018 by Hjalmar Nilsonne and Daniel Ek. Neko's vision is to create a healthcare system that can help people stay healthy through preventive…
Product: AI-driven, non-invasive full-body scanning service with app-based health insights
Recent valuation: $1.8B post-money (after Jan 2025 Series B)
Total disclosed funding: $330.85M (reported total)
Geographic expansion: Operations launched in London; first U.S. location announced for New York City (2026 planned)
Company Overview
Problem Domain
Preventive healthcare and early disease detection through non-invasive diagnostics and consumer-facing scanning services.
Founded
2018
Industry
Hospitals and Health Care
Funding Track Record
Series A- July 2023
€60M (~$65M)
Participation from Atomico, General Catalyst, and Prima Materia
Series B- January 2025
$260M
Post-money valuation reported at $1.8 billion
Investor Signal
“Backed by prominent venture investors including Lightspeed Venture Partners, Lakestar, Atomico, General Catalyst and Prima Materia (Daniel Ek's investment vehicle)”
BiotechnologyData and AnalyticsDeepTechHealthSoftware
$11M
Cleerly
🇺🇸Denver, US
HardwareHealthManufacturingMobile, Platforms, and AppsSoftware
$386M
xAI
🌍Remote
—
$37B
Who you are
An academic background in Data Science/Statistics/Analytics or related quantitative field, with 5+ years of experience as a data analyst
Expert-level SQL skills and strong proficiency with dbt (data build tool) for building and maintaining data models
Experience applying version control (Git) and CI/CD practices for analytics workflows
Strong Python skills for data analysis and demonstrated ability to establish analytics standards and frameworks in growing organizations
Experience with business intelligence tools and Azure Databricks or similar lakehouse platforms
Excellent stakeholder management and communication skills with ability to translate ambiguous business problems into well-defined analytical solutions
Prior experience working with healthcare data, medical device data, or similarly complex, regulated datasets
Further study to MSc level in Data Science, Statistics, or related field
Experience with experimentation methodologies and implementing data governance frameworks (ownership, lineage, data contracts)
Familiarity with modern data stack tools (Fivetran, dlt) and Unity Catalog or similar data governance platforms
What the job involves
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We are seeking a skilled Data Analyst to establish analytics capabilities and frameworks across the organization
You will build data models using our modern stack (dbt, Azure Databricks, Power BI), working across Finance, Medical Excellence, and Product—plus six other business areas—to enable data-driven decision-making company-wide
This role involves creating our single source of truth, implementing self-service analytics, and establishing data quality standards and governance frameworks
You will collaborate closely with diverse stakeholders—from medical doctors to operations teams and backend engineers—translating complex health data into actionable insights that drive clinical decisions and operational excellence
Our data team of analysts, scientists, and engineers operates in a remote-first culture with our Stockholm office as a collaborative hub
You'll define and standardize core business metrics and KPIs across the organization, ensuring consistency and eliminating duplicate definitions
Build and maintain centralized, governed BI dashboards and reports
Collaborate with data engineering to implement data quality standards, ownership frameworks, and lineage tracking in Unity Catalog
Partner with business stakeholders to understand their analytical needs and translate them into scalable, reusable data models using SQL, Python, and DBT
Support end-to-end analytical work — from problem framing and hypothesis design to delivering clear, decision-ready insights
Develop and document data contracts and enable self-service analytics while maintaining quality
Champion data literacy initiatives and enable teams to become more self-sufficient in their analytics
