Explore the progression of average salaries for graduates in Senior Software Engineer from 2020 to 2023 through this detailed chart. It compares these figures against the national average for all graduates, offering a comprehensive look at the earning potential of Senior Software Engineer relative to other fields. This data is essential for students assessing the return on investment of their education in Senior Software Engineer, providing a clear picture of financial prospects post-graduation.

🚀 Data Science Careers in 2025: Jobs and Salary Trends in Pakistan 🚀 Data Science is one of the fastest-growing fields, and by 2025, the demand for skilled professionals in Pakistan will only increase. If you’re considering a career in Data Science, here’s what you need to know about the top jobs and salary trends.

🔍 Top Data Science Jobs in 2025 1) Data Scientist Avg Salary: PKR 1.2M - 2.5M/year (Entry-Level), PKR 3M - 6M/year (Experienced) Skills: Python, R, Machine Learning, Data Visualization

2) Data Analyst Avg Salary: PKR 800K - 1.5M/year (Entry-Level), PKR 2M - 3.5M/year (Experienced) Skills: SQL, Excel, Tableau, Power BI

3) Machine Learning Engineer Avg Salary: PKR 1.5M - 3M/year (Entry-Level), PKR 4M - 7M/year (Experienced) Skills: TensorFlow, PyTorch, Deep Learning, NLP

4)Business Intelligence Analyst Avg Salary: PKR 1M - 2M/year (Entry-Level), PKR 2.5M - 4M/year (Experienced) Skills: Data Warehousing, ETL, Dashboarding

5) AI Research Scientist Avg Salary: PKR 2M - 4M/year (Entry-Level), PKR 5M - 10M/year (Experienced) Skills: AI Algorithms, Research, Advanced Mathematic

💡 Why Choose Data Science? High Demand: Every industry in Pakistan needs data professionals. Attractive Salaries: Competitive pay based on technical expertise. Growth Opportunities: Unlimited career growth in this field.

📈 Salary Trends Entry-Level: PKR 800K - 1.5M/year Mid-Level: PKR 2M - 4M/year Senior-Level: PKR 5M+ (depending on expertise and industry)

🛠️ How to Get Started? Learn Skills: Focus on Python, SQL, Machine Learning, and Data Visualization. Build Projects: Work on real-world datasets to create a strong portfolio. Network: Connect with industry professionals and join Data Science communities.

work_year: The year in which the data was recorded. This field indicates the temporal context of the data, important for understanding salary trends over time.

job_title: The specific title of the job role, like 'Data Scientist', 'Data Engineer', or 'Data Analyst'. This column is crucial for understanding the salary distribution across various specialized roles within the data field.

job_category: A classification of the job role into broader categories for easier analysis. This might include areas like 'Data Analysis', 'Machine Learning', 'Data Engineering', etc.

salary_currency: The currency in which the salary is paid, such as USD, EUR, etc. This is important for currency conversion and understanding the actual value of the salary in a global context.

salary: The annual gross salary of the role in the local currency. This raw salary figure is key for direct regional salary comparisons.

salary_in_usd: The annual gross salary converted to United States Dollars (USD). This uniform currency conversion aids in global salary comparisons and analyses.

employee_residence: The country of residence of the employee. This data point can be used to explore geographical salary differences and cost-of-living variations.

experience_level: Classifies the professional experience level of the employee. Common categories might include 'Entry-level', 'Mid-level', 'Senior', and 'Executive', providing insight into how experience influences salary in data-related roles.

employment_type: Specifies the type of employment, such as 'Full-time', 'Part-time', 'Contract', etc. This helps in analyzing how different employment arrangements affect salary structures.

work_setting: The work setting or environment, like 'Remote', 'In-person', or 'Hybrid'. This column reflects the impact of work settings on salary levels in the data industry.

company_location: The country where the company is located. It helps in analyzing how the location of the company affects salary structures.

company_size: The size of the employer company, often categorized into small (S), medium (M), and large (L) sizes. This allows for analysis of how company size influences salary.

In 2024, senior executives in the IT market reported the highest total annual compensation, with a median of over 127,388 thousand U.S. dollars. Developer advocates, managers, and developer experience engineers earned well over 100 thousand U.S. dollars annually. Site reliability engineers and cloud infrastructure engineers had median earnings of one thousand and 97 thousand U.S. dollars, respectively. At the lower end of the spectrum, academic researchers, front-end developers, and students earned less than 50 thousand U.S. dollars in total annual compensation.

Explore the progression of average salaries for graduates in Relevant Experience As A Senior System On Chip Application Engineer from 2020 to 2023 through this detailed chart. It compares these figures against the national average for all graduates, offering a comprehensive look at the earning potential of Relevant Experience As A Senior System On Chip Application Engineer relative to other fields. This data is essential for students assessing the return on investment of their education in Relevant Experience As A Senior System On Chip Application Engineer, providing a clear picture of financial prospects post-graduation.

Overview This dataset provides insights into salary distributions across various job classifications, enabling a deeper understanding of compensation trends across industries, experience levels, and geographical locations. It serves as a valuable resource for HR professionals, job seekers, researchers, and policymakers aiming to analyze pay scales, wage gaps, and salary progression trends.

Data Sources The data is aggregated from multiple employment and compensation reports, salary surveys, and publicly available job postings. It has been cleaned, standardized, and structured to ensure consistency and usability for analytical purposes.

Features Job Title: Specific title of the job (e.g., Data Analyst, Software Engineer, Marketing Manager).

Job Classification: Broad category of jobs (e.g., IT, Finance, Healthcare, Education).

Industry: The sector in which the job belongs (e.g., Technology, Banking, Retail).

Experience Level: Categorized as Entry-level, Mid-level, or Senior-level.

Education Requirement: Minimum qualification required for the job role.

Average Salary (INR/USD/Other Currency): The median or mean salary for a particular job classification.

Salary Range: The minimum and maximum salary offered for a role.

Location: Country or region where the job is based.

Employment Type: Full-time, Part-time, Contract, or Remote.

Company Size: Small, Medium, or Large enterprises.

Potential Use Cases Salary Benchmarking: Compare salary expectations across industries and job roles.

Career Planning: Identify lucrative career paths based on salary trends.

Wage Gap Analysis: Examine salary disparities by gender, location, or experience level.

Cost of Living Adjustments: Assess salaries relative to regional economic conditions.

HR and Recruitment Strategies: Optimize compensation packages to attract top talent.

Acknowledgments The dataset is compiled from various salary reports and job market research sources. Special thanks to contributors and organizations providing employment data for analysis.

License This dataset is shared for educational, research, and analytical purposes. Please ensure compliance with relevant data usage policies before any commercial applications.

Get Started The dataset can be explored using Python (Pandas), R, SQL, or visualization tools like Tableau and Power BI. Sample notebooks and analyses are available in the Kaggle notebook section.

This statistic shows data on the average annual salary of (level IV) software engineers in the information and communications technology (ICT) industry in Germany from 2011 to 2016. In 2016, a level IV software engineer in Germany earned an average of 80,859 euros per year.

A structured overview of the average, net, median, and minimum wage in Germany for 2025. This dataset combines original market research conducted by KUMMUNI GmbH with publicly available data from the German Federal Statistical Office. It includes values with and without bonuses, hourly minimum wage, and take-home pay after tax.

Analysis of ‘Engineering Graduate Salary Prediction’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/manishkc06/engineering-graduate-salary-prediction on 28 January 2022.

--- Dataset description provided by original source is as follows ---

Context

Engineering is the use of scientific principles to design and build machines, structures, and other items, including bridges, tunnels, roads, vehicles, and buildings. The discipline of engineering encompasses a broad range of more specialized fields of engineering, each with a more specific emphasis on particular areas of applied mathematics, applied science, and types of application. https://images.pexels.com/photos/414579/pexels-photo-414579.jpeg?auto=compress&cs=tinysrgb&dpr=1&w=500" alt="eng"> Engineering is a broad discipline that is often broken down into several sub-disciplines. Although an engineer will usually be trained in a specific discipline, he or she may become multi-disciplined through experience. Engineering is often characterized as having four main branches: chemical engineering, civil engineering, electrical engineering, and mechanical engineering. [Reference: Wikipedia]

Engineering Graduates in India India has a total 6,214 Engineering and Technology Institutions in which around 2.9 million students are enrolled. Every year on an average 1.5 million students get their degree in engineering, but due to lack of skill required to perform technical jobs less than 20 percent get employment in their core domain. [source of information: BWEDUCATION]

Objective

A relevant question is what determines the salary and the jobs these engineers are offered right after graduation. Various factors such as college grades, candidate skills, the proximity of the college to industrial hubs, the specialization one have, market conditions for specific industries determine this. On the basis of these various factors, your objective is to determine the salary of an engineering graduate in India.

Data Description

• ID: A unique ID to identify a candidate
• Salary: Annual CTC offered to the candidate (in INR)
• Gender: Candidate's gender
• DOB: Date of birth of the candidate
• 10percentage: Overall marks obtained in grade 10 examinations
• 10board: The school board whose curriculum the candidate followed in grade 10
• 12graduation: Year of graduation - senior year high school
• 12percentage: Overall marks obtained in grade 12 examinations
• 12board: The school board whose curriculum the candidate followed
• CollegeID: Unique ID identifying the university/college which the candidate attended for her/his undergraduate
• CollegeTier: Each college has been annotated as 1 or 2. The annotations have been computed from the average AMCAT scores obtained by the students in the college/university. Colleges with an average score above a threshold are tagged as 1 and others as 2.
• Degree: Degree obtained/pursued by the candidate
• Specialization: Specialization pursued by the candidate
• CollegeGPA: Aggregate GPA at graduation
• CollegeCityID: A unique ID to identify the city in which the college is located in.
• CollegeCityTier: The tier of the city in which the college is located in. This is annotated based on the population of the cities.
• CollegeState: Name of the state in which the college is located
• GraduationYear: Year of graduation (Bachelor's degree)
• English: Scores in AMCAT English section
• Logical: Score in AMCAT Logical ability section
• Quant: Score in AMCAT's Quantitative ability section
• Domain: Scores in AMCAT's domain module
• ComputerProgramming: Score in AMCAT's Computer programming section
• ElectronicsAndSemicon: Score in AMCAT's Electronics & Semiconductor Engineering section
• ComputerScience: Score in AMCAT's Computer Science section
• MechanicalEngg: Score in AMCAT's Mechanical Engineering section
• ElectricalEngg: Score in AMCAT's Electrical Engineering section
• TelecomEngg: Score in AMCAT's Telecommunication Engineering section
• CivilEngg: Score in AMCAT's Civil Engineering section
• conscientiousness: Scores in one of the sections of AMCAT's personality test
• agreeableness: Scores in one of the sections of AMCAT's personality test
• extraversion: Scores in one of the sections of AMCAT's personality test
• nueroticism: Scores in one of the sections of AMCAT's personality test
• openess_to_experience: Scores in one of the sections of AMCAT's personality test

**Note: **To give you more context AMCAT is a job portal.

Acknowledgemet

I would like to thank ‘Aspiring Minds Research’ for making this dataset available publicly.

Inspiration

The data can be used not only to make an accurate salary predictor but also to understand what influences salary and job titles in the labour market. It’s up to you to explore things.

This Dataset is also available at DPhi

--- Original source retains full ownership of the source dataset ---

Average hourly and weekly wage rate, and median hourly and weekly wage rate by National Occupational Classification (NOC), type of work, gender, and age group.

This dataset is a listing of all active City of Chicago employees, complete with full names, departments, positions, employment status (part-time or full-time), frequency of hourly employee –where applicable—and annual salaries or hourly rate. Please note that "active" has a specific meaning for Human Resources purposes and will sometimes exclude employees on certain types of temporary leave. For hourly employees, the City is providing the hourly rate and frequency of hourly employees (40, 35, 20 and 10) to allow dataset users to estimate annual wages for hourly employees. Please note that annual wages will vary by employee, depending on number of hours worked and seasonal status. For information on the positions and related salaries detailed in the annual budgets, see https://www.cityofchicago.org/city/en/depts/obm.html

Data Disclosure Exemptions: Information disclosed in this dataset is subject to FOIA Exemption Act, 5 ILCS 140/7 (Link:https://www.ilga.gov/legislation/ilcs/documents/000501400K7.htm)

The global developer population is expected to reach 28.7 million people by 2024, an increase of 3.2 million from the number seen in 2020. According to the source, much of this growth is expected to occur in China, where the growth rate is between six percent to eight percent heading up to 2023. How much do software developers earn in the U.S.? Software developers work within a wide array of specialties, honing their skills in different programming languages, techniques, or in disciplines such as design. The average salary of U.S.-based designers working in software development reached 108 thousand U.S. dollars as of June 2021, while this figure climbs to 165 thousand U.S. dollars for engineering managers. Salaries are highly dependent on location, however, with an entry-level developer working in the San Francisco/Bay area earning an average of 44.79 percent more than their counterparts starting out in Austin. JavaScript and HTML/CSS still the most widely used languages While programming languages continue to emerge or fall out of favor, JavaScript and HTML/CSS are mainstays of the coding landscape. In a global survey of software developers, over 60 percent of respondents reported using JavaScript, and HTML/CSS. SQL, Python, and Java rounded out the top five.

Detailed labour market outcomes by educational characteristics, including detailed occupation, hours and weeks worked and employment income.