Use Case

Data Facts of Data Developer Salary in 2024

Julian Zhou

Jun 18, 2024

About the dataset

  • Name: Data Developer Salary in 2024

  • Source: Kaggle

AI Data Analysis powered by Powerdrill AI

Relevant Inquiries

  1. Salary Analysis by Job Title: What are the average salaries for different job titles in the dataset?

  2. Experience Level Impact: How does experience level (SE, MI, EN, EX) affect the salary in USD?

  3. Employment Type Comparison: What is the distribution of salaries across different employment types (FT, PT, CT, FL)?

  4. Geographical Salary Differences: How do salaries vary by employee residence and company location?

  5. Remote Work Influence: Is there a correlation between remote work ratio and salary?

  6. Company Size Effect: How does the size of the company (M, L, S) impact the salary?

  7. Yearly Trends: Are there any noticeable trends in salaries over the years from 2020 to 2024?

  8. Currency Conversion: How do salaries in different currencies compare when converted to USD?

  9. Top Paying Roles: Which job titles have the highest average salaries?

  10. Salary Distribution: What is the distribution of salaries within the dataset, and are there any outliers?

These inquiries can help in understanding various aspects of the dataset and provide insights into salary trends and factors affecting them.


Salary Analysis by Job Title: What are the average salaries for different job titles in the dataset?



Conclusion

  • Average Salary by Job Title: The dataset contains information on the average salaries for various job titles related to the field of artificial intelligence.

  • Statistical Overview:

    • The mean average salary across all job titles is $214,281.13.

    • There is a significant standard deviation of $317,398.06, indicating a wide range in salaries.

    • The lowest reported average salary is 40,000**, and the **highest is 3,000,000.

  • Sample Data Insights:

    • An AI Architect earns an average salary of $252,002.

    • An AI Developer has an average salary of $134,684.

    • The average salary for an AI Engineer is $163,627.

    • An AI Product Manager earns around $141,767 on average.

    • An AI Programmer stands out with a significantly higher average salary of $764,401.

  • Data Scope: The above figures are based on a subset of the dataset, which includes 155 job titles.


Experience Level Impact: How does experience level (SE, MI, EN, EX) affect the salary in USD?



Conclusion

Based on the provided context and visualized analytical data, the impact of different experience levels on the salary in USD is as follows:

  • Entry Level (EN): The mean salary for individuals with entry-level experience is the lowest among the groups, at $92,327.41.

  • Mid Level (MI): Mid-level experienced individuals have a higher mean salary than entry-level, at $125,923.00.

  • Senior Level (SE): Senior-level experience leads to a further increase in the mean salary, which is $163,663.00.

  • Executive Level (EX): Executives have the highest mean salary, significantly more than other experience levels, at $195,264.28.

The bar chart visualization confirms the ascending trend in mean salary with increasing experience levels, illustrating a clear correlation between experience and compensation.


Employment Type Comparison: What is the distribution of salaries across different employment types (FT, PT, CT, FL)?



Conclusion

Based on the provided context and data, the distribution of salaries across different employment types can be summarized as follows:

  • Contract (CT):

    • Mean Salary: $112,578

    • Standard Deviation: $91,676

    • Minimum Salary: $25,500

    • 25th Percentile: $50,000

    • Median Salary (50th Percentile): $93,856

    • 75th Percentile: $121,902

    • Maximum Salary: $416,000

  • Freelance (FL):

    • Mean Salary: $49,220.86

    • Standard Deviation: $24,997.26

    • Minimum Salary: $20,000

    • 25th Percentile: $31,892.25

    • Median Salary (50th Percentile): $47,777.50

    • 75th Percentile: $57,500

    • Maximum Salary: $100,000

  • Full-Time (FT):

    • Mean Salary: $149,988

    • Standard Deviation: $68,351

    • Minimum Salary: $15,000

    • 25th Percentile: $102,225

    • Median Salary (50th Percentile): $141,525

    • 75th Percentile: $185,900

    • Maximum Salary: $800,000

  • Part-Time (PT):

    • Mean Salary: $83,750.2

    • Standard Deviation: $61,774.4

    • Minimum Salary: $15,966

    • 25th Percentile: $35,028.5

    • Median Salary (50th Percentile): $66,451.5

    • 75th Percentile: $121,158

    • Maximum Salary: $291,340

Key Observations:

  • Full-Time (FT) positions have the highest mean salary and the widest range of salaries, indicating a diverse set of roles and industries.

  • Freelance (FL) positions have the lowest mean salary and the narrowest range, suggesting these roles may be more uniform in compensation or concentrated in lower-paying sectors.

  • Contract (CT) and Part-Time (PT) positions have mean salaries that are closer to each other, but contract roles have a higher maximum salary, which could indicate the presence of high-paying specialized contract roles.

  • The standard deviation is highest for full-time roles, which again reflects the wide variation in salaries within this employment type.

Visual Representation: The box plot visualization would show the median (50th percentile), quartiles (25th and 75th percentiles), and range (min to max) for each employment type, providing a visual summary of the salary distributions. The mean and standard deviation are not typically shown on a box plot but are important for understanding the overall distribution characteristics.


Geographical Salary Differences: How do salaries vary by employee residence and company location?

Analyze the dataset to determine how salaries vary based on the residence of the employee. This involves grouping the data by 'employee_residence' and calculating the average salary in USD for each group.


Analyze the dataset to determine how salaries vary based on the location of the company. This involves grouping the data by 'company_location' and calculating the average salary in USD for each group.


Conclusion on Salary Variation Based on Employee Residence and Company Location

Employee Residence Salary Analysis:

  • The dataset contains 88 unique employee residences.

  • The average salary across these residences is USD 78,945.56 with a standard deviation of USD 47,919.15.

  • Salaries range from a minimum of USD 15,000 to a maximum of USD 300,000.

  • The first five records show residences such as AD, AE, AM, AR, and AS with average salaries of USD 50,745, USD 86,000, USD 33,500, USD 58,461.5, and USD 45,555 respectively.

Company Location Salary Analysis:

  • The dataset includes 77 unique company locations.

  • The average salary for these locations is USD 76,170.33 with a standard deviation of USD 45,233.34.

  • Salaries range from a minimum of USD 16,000 to a maximum of USD 300,000.

  • The first five records show locations such as AD, AE, AM, AR, and AS with average salaries of USD 50,745, USD 86,000, USD 50,000, USD 62,444.4, and USD 31,684.3 respectively.

Visual Analysis:

  • The provided bar charts visually represent the average salaries for both employee residence and company location.

  • The charts show significant variation in average salaries across different locations, with some locations having notably higher average salaries than others.

  • The peaks in the bar charts indicate locations with exceptionally high average salaries, while other locations have more moderate salary averages.

Key Observations:

  • There is a wide range of average salaries based on both employee residence and company location, indicating geographical salary disparities.

  • The highest salaries are not necessarily in the same locations for employee residence and company location, suggesting that other factors may influence salary levels.

  • Further analysis could include examining the cost of living, industry sectors, or economic conditions in each location to better understand the context behind these salary figures.

Recommendations for Users:

  • Users should consider the cost of living and local economic conditions when comparing salaries across different locations.

  • For a more detailed analysis, users may want to segment the data by job role, industry, or experience level to gain insights into specific salary trends.

  • Additional data such as company size, employment benefits, and currency fluctuations could provide a more comprehensive understanding of the salary landscape.


Remote Work Influence: Is there a correlation between remote work ratio and salary?


Conclusion

  • Correlation Coefficient: The correlation between 'remote_ratio' and 'salary' is 0.0210251.

  • Strength of Relationship: This value indicates a very weak positive correlation.

  • Statistical Significance: The context does not provide information on statistical significance (p-value), so we cannot definitively say if the correlation is significant.

  • Implication: With the given data, it can be concluded that there is no meaningful relationship between the remote work ratio and salary.


Company Size Effect: How does the size of the company (M, L, S) impact the salary?



Conclusion

Based on the provided context and visualized data, we can draw the following conclusions about the impact of company size on salary:

  • Large Companies (L): The average salary for employees in large companies is the highest among the three categories, with an average salary of $308,404.

  • Medium Companies (M): Employees in medium-sized companies have the lowest average salary, which is $152,414.

  • Small Companies (S): Small companies offer an average salary that is higher than that of medium companies but lower than large companies, with an average salary of $284,438.

The bar chart visualization supports these findings by showing the average salary for each company size category. The tallest bar represents large companies, followed by small companies, and the shortest bar represents medium companies. This suggests that, in this dataset, company size does have a significant impact on the average salary, with larger companies generally offering higher salaries.


Yearly Trends: Are there any noticeable trends in salaries over the years from 2020 to 2024?




Conclusion

  • Trend Analysis: The average salary has shown a general upward trend from 2020 to 2024.

  • Yearly Breakdown:

    • 2020: The average salary was $102,251.

    • 2021: There was a slight decrease to an average salary of $99,922.

    • 2022: A significant increase occurred, with the average salary rising to $134,350.

    • 2023: The upward trend continued, reaching the highest average salary of $153,733.

    • 2024: A slight decrease from the previous year, with an average salary of $150,564.

  • Key Observations:

    • The largest increase in average salary occurred between 2021 and 2022.

    • The peak average salary was observed in 2023.

    • There was a minor decline in the average salary from 2023 to 2024, but it remained significantly higher than the years 2020 and 2021.

Visual Representation: The provided line chart visually supports the conclusion, showing the fluctuations and overall growth in average salaries over the specified years.


Currency Conversion: How do salaries in different currencies compare when converted to USD?



Conclusion

Comparison of Salaries in Different Currencies Converted to USD:

  • Highest Average Salary in USD: The currency with the highest average salary when converted to USD is the CHF (Swiss Franc), with an average salary of $137,188.

  • Lowest Average Salary in USD: The currency with the lowest average salary in USD is the BRL (Brazilian Real), with an average salary of $26,095.80.

  • Variability in Salaries: The standard deviation of salaries in USD varies significantly across currencies, indicating different levels of salary dispersion within each currency group. For example, the CAD (Canadian Dollar) has a standard deviation of $51,766.30, suggesting a wide range of salaries in USD among Canadian earners.

  • Data Inconsistencies: There is a missing value (NaN) for the standard deviation of salaries in USD for the CLP (Chilean Peso), indicating incomplete data for that currency.

Visual Analysis:

  • The provided bar chart visually represents the average salary in USD for each currency.

  • The chart clearly shows that some currencies, like the CHF, have a much higher average salary in USD compared to others, such as the BRL or CLP.

  • The visual representation allows for an easy comparison across different currencies, highlighting the disparities in earning power when standardized to a single currency (USD).

Considerations for Further Analysis:

  • To enhance understanding, it would be beneficial to analyze the cost of living associated with each currency to contextualize the salary figures.

  • Additionally, examining the median salary could provide insights into the typical earnings, as the mean can be skewed by extreme values.

  • The presence of outliers could also be investigated to ensure that the average salary figures are representative of the general population earning in each currency.


Top Paying Roles: Which job titles have the highest average salaries?


Conclusion

  • Highest Average Salary: The job title with the highest average salary in the provided dataset is AI Architect, with an average salary of $252,551.

  • Other Notable Salaries: Following the AI Architect, the job titles with the next highest average salaries are AI Engineer at 162,731** and **AI Product Manager** at **141,767.

  • Comparison with AI Developer: The AI Developer position holds an average salary of $135,467, which is lower than the AI Architect and AI Engineer but higher than the AI Product Manager.

  • AI Programmer Salary: The AI Programmer has the lowest average salary among the top 5 job titles listed, at $62,042.


Salary Distribution: What is the distribution of salaries within the dataset, and are there any outliers?



Conclusion

Salary Distribution Analysis:

  • The mean salary is 4,478,442.24 (local currency), with a high standard deviation of 11,430,757.11, indicating significant variability in salary values.

  • The mean salary in USD is 208,788.15, with a standard deviation of 266,748.14, also showing considerable variability.

  • The minimum salary recorded is 14,000 (local currency) and 15,000 USD.

  • The maximum salary recorded is a substantial 30,400,000 (local currency) and 800,000 USD.

  • The 25th percentile (Q1) for salary is 101,763 (local currency) and 101,125 USD, the median (50th percentile) is 142,200 (local currency) and 141,300 USD, and the 75th percentile (Q3) is not displayed in the provided data.

Outliers Identification:

  • There are 345 outliers in the 'Salary' column and 283 outliers in the 'Salary in USD' column, as per the provided statistics.



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