Data Science, Machine Learning and AI

See what work of data science related specialists looks like. Check what are the average salaries in this role. Find out what are the most popular Technologiess and techniques.

Polish IT Community Report 2025 Hero Image

Respondent Profile

Subroles
Data Science
57.3%
ml-ai-engineer
42.7%
Gender
Male
74.2%
Female
25.8%
Age
18 - 24 years old
11.2%
25 - 29 years old
50.6%
30 - 34 years old
22.5%
35 - 39 years old
12.4%
40+ years
3.4%
Education
Master's degree (Master, Master of Science in Engineering)
51.7%
Bachelor's degree (licentiate, engineer)
18.0%
Doctoral studies
12.4%
Company size
Small company (up to 50)
22.5%
Medium-sized company (51-500)
23.6%
Large company (501-5,000)
22.5%
Very large company (more than 5,000)
31.5%
Level of experience
Intern
1.1%
Junior
14.6%
Mid / Regular
47.2%
Senior
29.2%
Tech Lead / Team Lead
5.6%
Mid-level Manager
1.1%
Director / C-level
1.1%
Experience level vs. years of experienc
Senior
6.9 years
Mid / Regular
4.0 years
Junior
1.4 years
What are your career aspirations?
I want to stay in my specialization
85.7%
I want to change my specialization within IT
6.0%
I do not want to work in IT in the future
4.8%
I don't know.
3.6%
Do you want to manage a team in the future?
I don't know.
18.2%
Yes
38.6%
No
21.6%
It doesn't matter to me
21.6%

Comment

Since 2023, when the Data Science, Machine Learning, and AI specialization first appeared in the report with an additional detailed report, the relatively small community of specialists in this field (2 to 3% of respondents – only IT architects are fewer) has consistently been characterized by the highest level of education: in 2025, almost 52% of respondents have a second-degree education, and over 12% hold a PhD (with the average for this level of education not exceeding 1.5% in the entire surveyed population).

The specialty is still young—both in terms of work experience (an average of 5 years, three times less than, for example, IT Architects – although the rapid development path may also be the result of the highest involvement in using AI/ML tools) and age: almost 51% are in the 25-29 age group (the share of this age group among all respondents is about 30%).

A fast career path, interest in their field, and the lowest professional burnout also seem to determine the highest "loyalty" to their specialty: over 85% want to remain in it, even though it is not the highest paid: salaries remain in 4th place, which is in the middle-range. Women’s participation is also mid-range: with an average participation of about 20%, nearly 26% are women in this group.

In over 31% of cases, employment for Data Science, ML, and AI specialists is at very large companies (based on practical market observations, it can be assumed these are mostly IT departments or divisions of "non-IT" companies), while for the entire surveyed population, the dominant place of employment—with a similar percentage share—is medium-sized companies.

dr Tomasz Kulisiewicz
dr Tomasz Kulisiewicz
ICT Market Analyst
Polskie Towarzystwo Informatyczne
Polskie Towarzystwo Informatyczne

Technologies

Daily tasks at work
Creating and training models
35.3%
Implementation of algorithms and models
19.6%
Data collection and preparation
19.6%
Data analysis and exploration
17.6%
Data management
5.9%
Data visualization
2.0%
Implementation of algorithms and models
44.7%
Creating and training models
31.6%
Data collection and preparation
7.9%
Data analysis and exploration
7.9%
Data management
7.9%
What programming languages do you use in your work?
Python
94.1%
SQL
58.8%
Python
100.0%
SQL
26.3%
Mainly used techniques
Statistical analysis
78.4%
Machine Learning
76.5%
Supervised learning
62.7%
Deep Learning
43.1%
NLP
37.3%
Fine-tuning LLM
29.4%
Unsupervised learning
29.4%
Machine Learning
89.5%
Deep Learning
65.8%
Supervised learning
57.9%
Statistical analysis
55.3%
NLP
50.0%
Fine-tuning LLM
50.0%
Unsupervised learning
34.2%
Transfer learning
31.6%
Mainly used tools
Pandas
94.1%
Jupyter Notebook
78.4%
Scikit-learn
72.5%
Excel
52.9%
PyTorch
33.3%
TensorFlow
23.5%
Keras
21.6%
Pandas
91.9%
Jupyter Notebook
81.1%
Scikit-learn
64.9%
PyTorch
62.2%
Torch
40.5%
TensorFlow
32.4%
Excel
29.7%
Keras
29.7%

Salaries

AVG
MEDIAN
Salaries by job type - average
UoP, UZ, and UD - net amount; B2B - net on the invoice.
Data Science
9 994 PLN
ml-ai-engineer
26 214 PLN
Data Science
21 800 PLN
AVG
MEDIAN
Salaries by job type - median
UoP, UZ, and UD - net amount; B2B - net on the invoice.
Data Science
8 600 PLN
ml-ai-engineer
22 500 PLN
Data Science
18 000 PLN
AVG
MEDIAN
Earnings versus experience - average
UoP, UZ, and UD - net amount; B2B - net on the invoice.
Senior
12 675 PLN
Mid / Regular
9 250 PLN
Senior
30 100 PLN
Mid / Regular
16 022 PLN
AVG
MEDIAN
Salaries and experience - median
UoP, UZ, and UD - net amount; B2B - net on the invoice.
Senior
12 500 PLN
Mid / Regular
8 600 PLN
Senior
30 000 PLN
Mid / Regular
15 200 PLN
Honorary Patronage
Content Partners
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