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.

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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%

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
Data Science
9 994 PLN
ml-ai-engineer
26 214 PLN
Data Science
21 800 PLN
AVG
MEDIAN
Salaries by job type - median
Data Science
8 600 PLN
ml-ai-engineer
22 500 PLN
Data Science
18 000 PLN
AVG
MEDIAN
Earnings versus experience - average
Senior
12 675 PLN
Mid / Regular
9 250 PLN
Senior
30 100 PLN
Mid / Regular
16 022 PLN
AVG
MEDIAN
Salaries and experience - median
Senior
12 500 PLN
Mid / Regular
8 600 PLN
Senior
30 000 PLN
Mid / Regular
15 200 PLN
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