Data scientist
| Highest | $10,000 / mo · Switzerland |
|---|---|
| Experience | 2–4 yrs |
| Degree | Required |
| First paycheck | 3-year bachelor |
Pay in the destination countries
Monthly, in US dollars. Each country is an Imora admission package — open one for that route's fees, language requirement and deadline.
| Country | Monthly |
|---|---|
| SwitzerlandIELTS 6.5 · CHF 0.9–8k | $10,000max |
| United StatesTOEFL 80–100 · $10–70k | $9,500 |
| NorwayIELTS 6.0–6.5 · NOK 130–260k | $7,600 |
| DenmarkIELTS 6.5 · DKK 45–135k | $6,450 |
| IrelandIELTS 6.0–6.5 · €10–25k | $6,250 |
| Hong KongIELTS 6.0–6.5 · HK–200k | $5,900 |
What does the day look like?
Your day starts with data access in SQL, then cleaning and preparation in Python with pandas and scikit-learn. Then you build models with regression, gradient boosting, and neural networks in PyTorch or TensorFlow, track experiments in MLflow, version code in Git, orchestrate pipelines with Airflow, and work on AWS, Azure, or Google Cloud Platform. You explain results in dashboards built in Tableau, Power BI, or Looker, plus notebooks and written memos.
Model fitting is a small share of the day. Most time goes to finding data, cleaning data, validating results, writing data tests, reviewing code, documenting assumptions, and explaining findings to product, finance, marketing, or risk teams. Deployment and monitoring are shared with engineering. Posts are full time, office or hybrid. Shift work and night work are not typical. Teams behind live products for fraud, pricing, recommendations, or operations carry on-call, with incident response outside standard hours. Remote posts add overlap hours with the hiring team time zone.
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