Fully remote data-scientist roles, refreshed daily. The companies here work with explicit hypothesis templates, documented experiments and notebook reviews as an async default.
Job title
Data Scientist Remote Jobs
85
active positions
1
new in 7 days
169,125 EUR
Avg. salary/year
Open positions
- No positions for this job title currently
Salary expectations
Average: 169,125 EUR per year – based on 0 job listings.
Experience
Avg. salary
Senior (5–9 yrs)
190,000 EUR
Lead / Staff (10+ yrs)
162,167 EUR
In-demand skills
Top skills from 0 job listings
Go
0%
Python
0%
AWS
0%
Rust
0%
Azure
0%
ETL
0%
CI/CD
0%
SRE
0%
Docker
0%
Kafka
0%
Hiring companies
NIQ (NielsenIQ) · 15 Sofi · 11 Intercom · 7 Usaa · 5 Aircall · 4 Humana · 4 Perplexity · 4 Aig · 3 Muttdata · 3 Gusto · 3 Gaig · 2 Algo1 · 2
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What shapes remote data-science roles
In a remote setup, DS work becomes more documented: every hypothesis has a brief, every experiment a pre-registration doc, every model a model-card entry. Async reviews via notebook PRs and Loom walkthroughs are the default.
Typical scope: experiment design for product hypotheses, A/B-test analysis, forecasting, feature engineering and model training. Senior roles add roadmap stewardship and mentorship.
How to apply successfully
- Bring 2–3 concrete case studies: business problem → method → result → impact (in metrics).
- Add a writing sample: an experiment postmortem or an insight doc.
- Tooling specifically: dbt, Snowflake/BigQuery, Python stack (pandas, scikit-learn, statsmodels). LLM integration is increasingly common.
- Statistical rigour: at senior+ expect questions on causal inference, Bayesian methods or uplift modelling.
Frequently asked questions
- Which industries hire remote DS heavily?
- Top: B2B SaaS (product analytics), FinTech (risk modelling), HealthTech (clinical studies), AI companies (applied research). E-commerce roles often blend with ML engineering.
- How is compensation structured?
- EU-remote: 70–110k EUR mid, 110–160k EUR senior, 160–230k EUR staff. US-remote: 130–190k USD mid, 190–280k USD senior, 280–420k USD staff. AI/LLM focus currently adds +15–30%.
- DS vs ML Engineer — what is the difference?
- DS = hypotheses + models + insights for product/business decisions. ML Engineer = production-grade ML systems. Crossover growing; many companies no longer split the roles.
- Do I need a PhD?
- For applied-DS roles, rarely required. For research scientist roles at AI companies, often expected. Filter by "research" vs "applied" to see the expectation early.