Tasks in the US, Canada, the UK and the EU, with the rate on every one. See open tasks
No Data Scientist task is tied to Lithuania this week. The typical rate for a senior Data Scientist here is €30 an hour, built from a market median wage of €19.59. At five hours a week that is about €650 a month.
Remote tasks and tasks tied to a city in Lithuania.
New tasks arrive daily. Leave an e-mail and a recruiter writes the day one opens in Lithuania, or sends remote tasks from nearby that you can take from home.
Tell me when one opensFully remote tasks from other countries in the European Union. The rate is shown in the currency of the task.
Manager · Data Scientist
Omnichannel retailer selling outdoor gear · 201–500 employees
€80–€94 / hour
About €520–€1,040 in total
Manager · Data Scientist
Aerospace supplier in avionics · 5,000+ employees
€34–€38 / hour
About €430–€860 in total
Senior · Data Scientist
Analytics software company for schools · 5,000+ employees
€47–€54 / hour
About €510–€1,010 a month
Senior · Data Scientist
B2B media company covering technology · 201–500 employees
€43–€53 / hour
About €290–€580 in total
Senior · Data Scientist
Fashion retailer selling furniture · 201–500 employees
€23–€29 / hour
About €620 a month at 6 h a week
Director · Data Scientist
Performance marketing agency for consumer brands · 501–1,000 employees
€60–€73 / hour
About €400–€800 in total
Employee wage percentiles for the role. Contractors on Deftridge earn more than the median because they carry their own costs.
| Percentile | Per hour | 5 h a week, per month | Full time, per year |
|---|---|---|---|
| 10th | €10.94 | €240 | €22,800 |
| 25th | €14.28 | €310 | €29,700 |
| Median | €19.59 | €420 | €40,700 |
| 75th | €23.81 | €520 | €49,500 |
| 90th | €32.00 | €690 | €66,600 |
Source: Eurostat, 2022; aged to October 2026 with a wage index and calibrated on posted pay. Method.
| Level | Per hour | Per month at 5 h/week |
|---|---|---|
| Senior | €30 | €650 |
| Manager | €35 | €760 |
| Director | €40 | €870 |
Applied data science part-time: models for forecasting, scoring or segmentation, with results the business can use. Usual tools: Python, SQL, Jupyter, scikit-learn.
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