Data Scientist salary in Lithuania

The average data scientist salary in Lithuania in 2022 is EUR 38,100 per year (EUR 3,175 per month, or EUR 733 per week). This figure represents gross annual earnings before income tax and social contributions. Source: ILO / Life Indexed estimate.

Data Scientists in Lithuania earn between EUR 24,800 and EUR 55,200 per year in 2022. The spread reflects differences in experience level, employer size, sector (public vs private), and geographic location within the country.

A data scientist in Lithuania earns approximately EUR 3,175 per month (gross) in 2022, based on an annual average of EUR 38,100. Monthly take-home pay will be lower after income tax and social security deductions, which vary by individual circumstances and applicable tax brackets in Lithuania.

Entry-level data scientists in Lithuania typically earn between EUR 24,800 and EUR 32,400 per year in 2022. Salaries at the junior level are generally 15–35% below the national average, increasing with professional certifications, years of experience, and specialisation.

Yes. Based on available data, Data Scientist salaries in Lithuania have grown by approximately 23% between 2022 and 2026, reflecting ongoing demand and wage growth trends.

Among Europe countries in our dataset, Luxembourg offers the highest average data scientist salary at EUR 83,800 per year in 2022. Lithuania ranks 9 in the region with EUR 38,100/yr.

Whether EUR 38,100 per year is a good data scientist salary in Lithuania depends on cost of living, location, and career stage. This figure represents the 2022 national average — earners above this level are in the upper half of the pay distribution for this occupation. Factors that influence individual compensation include employer type (multinational vs. local), city (capital cities typically pay 10–25% more), qualifications, and years of experience.

Lithuania's data scientist salary of EUR 38,100/yr is below all other Europe countries tracked for this occupation in 2022. Differences across countries reflect purchasing power, labour market conditions, cost of living, and local demand for this role.