Table 1

Attribute	Description
ID_Number	Unique identifier assigned to each individual.
Name Surname	Full name of the individual.
Gender	The individual's gender.
Age	The current age of the individual.
Email	The individual's email address.
Phone	The individual's contact phone number.
City	City of residence.
District	District within the city of residence.
Rol_Category	The category of the job role.
Rol	Specific job position.
Years_of_Experience	Total number of years the person has worked professionally (float).
Title	Combined seniority and role.
Education_Level	Highest level of education attained (e.g., Bachelor's, Master's, Ph.D.).
Field of Education	The field or major studied.
Graduation Year	Year the individual completed their most recent degree.
Start Date	Date the individual started their current job.
Last Promotion Date	Date of the most recent promotion in their career.
Company	Name of the company where the person works.
Company Size	Classes such as Startup, Small, Medium, Corporate.
Industry	Sector or industry the company operates in.
Work Style	Mode of working (e.g., full time, part time).
Remote Work Rate	Percentage of time worked.
Technologies Used	List of tools the individual uses.
Main Programming Language	The primary programming language they work with.
English Level	Proficiency in English (e.g., Beginner, Intermediate, Advanced, Native).
Other Languages	Any other languages the individual speaks and their proficiency.
Certifications	Professional certificates earned.
LinkedIn Profile	URL to their LinkedIn account.
GitHub Profile	URL to their GitHub account or portfolio.
Total Number of Projects	Count of completed or contributed projects.
Annual Leave Days	Number of leave days allotted per year.

Table 1: Attributes and their descriptions

Table 2

Attribute	Description
Salary	Current annual or monthly salary.
Seniority	Level of experience or seniority.
Birth_year	The year the individual was born.
Technical Skill Score	0-100 points based on experience and certification.
Soft Skill Score	0-100 points based on role and seniority.

Table 2: Derived attributes and their descriptions

Table 3

Column	Description
Seniority	Intern (0) → Director (7)
Education_Level	High School (0) → PhD (4)
English_Level	Beginner (0) → Native Language (4)
Gender	Female (0), Male (1)

Table 3: The converted categories and their numerical values

Table 4

Models	Hyperparameter ranges
Voting	RR (“Alpha”: [0.1])RF (“N_Estimators”: [100],“Random_State”: [42])CatBoost (“Depth”:[4]“Iterations”:[100]“Learning_Rate”:[0.1])
Stacking	RR ( “Alpha”: [0.1])RF (“N_Estimators”: [100], “Random_State”:[42])CatBoost(“Iterations”:[500], “Learning_Rate”:[0.1], “Depth”:[6], “Verbose”: [0], “Random_State”: [42])
Ridge	“Alpha”: [0.1 - 10]
DT	“Max_Depth”: [2 – 10] “Min_Samples_Split”: [2 – 10]
RF	“N_Estimators”: [50 - 150]“Min_Samples_Split”: [2]“Max_Depth”: [4 - 10]“Leaf_Node”: [250]
Grid Search CV (for RF)	“N_Estimators”: [50 - 150] “Max_Depth”: [4 - 8] “Min_Samples_Split”: [2 - 10]
SVM	“C”: [0.1 - 10]“Epsilon”: [0.01 - 0.2]
CatBoost	“Iterations”: [100 – 500]“Learning_Rate”: [0.01 – 0.3]“Depth”: [4 – 10]“I2_Leaf_Reg”:[3]“Random_State”: [42]“Verbose”: [0]“Early_Stopping_Rounds”: [50]
AdaBoost	“Max_Depth”:[4]“N_Estimators”:[100]“Learning_Rate”:[1.0]“Random_State”:[42]

Table 4: The hyperparameter ranges of the models

Table 5

Model	MAE	MAPE	R^2
LR	2300	9.31%	0.936
RR	2150	9.28%	0.936
DT	0	0	0.1000
RF	1820	2.60%	0.993
AdaBoost	2400	10.31%	0.937
Voting	1400	5.66%	0.973
Stacking	1000	4.00%	0.975
CatBoost	1450	6.10%	0.910
SVM	1900	8.80%	0.890

Table 5: The MAE, MAPE and R^2 values of the developed models

Table 6

Model	Model Training Runtime (ms)	Explainability
LR	170 ms	High
RR	185 ms	High
DT	190 ms	Intermediate (Overfit)
RF	2350 ms	Intermediate
AdaBoost	3250 ms	Low
Voting	5650 ms	Intermediate
Stacking	5000 ms	Intermediate
CatBoost	9700 ms	High
SVM	19500 ms	Low

Table 6: The Model Training Runtime (ms) and Explainability values of the developed models

Tables at a glance