The salary of a Top Data Scientist in the United States varies depending on several factors, including experience, location, education level, marketing trend and company sizes.
As of April 01, 2025, the average hourly pay of Top Data Scientist in the United States is $131. While Salary.com is seeing that the highest pay for Top Data Scientist in the US can go up to $156 and the lowest down to $115, but most earn between $123 and $144. Salary.com shows the average base salary (core compensation), as well as the average total cash compensation for the job of Top Data Scientist in the United States.
| Annual Salary |
Monthly Pay |
Weekly Pay |
Hourly Wage |
|
| 75th Percentile | $144 | $12 | $3 | $0 |
| Average | $131 | $11 | $3 | $0 |
| 25th Percentile | $123 | $10 | $2 | $0 |
As of April 01, 2025, Salary.com is seeing that an entry-level Top Data Scientist with under 1 year experience makes about $261,997. With less than 2 years of experience, a mid-level Top Data Scientist makes around $263,578. After 2-4 years, the Top Data Scientist pay rises to about $265,687. Those senior Top Data Scientist with 5-8 years of experience earn roughly $268,849, and those Top Data Scientist having 8 years or more experience is expected to earn about $272,803 on average.
| Levels | Salary |
|---|---|
| Entry Level Top Data Scientist | $261,997 |
| Intermediate Level Top Data Scientist | $263,578 |
| Senior Level Top Data Scientist | $265,687 |
| Specialist Level Top Data Scientist | $268,849 |
| Expert Level Top Data Scientist | $272,803 |
| Entry Level | 4% |
| Mid Level | 3% |
| Senior Level | 3% |
| Top Level | 1% |
| Experienced | 0% |
Salaries in the United States can vary significantly from state to state due to a multitude of factors, including cost of living, local economic conditions, and industry presence.
For example, as of April 01, 2025, the average yearly salary of Top Data Scientist is $300,902 in California and in Massachusetts, the average annual salary goes to $296,892. While in New Jersey, a Top Data Scientist earns $295,691 per year.
What Am I Worth?
Salaries in the United States can vary significantly from city to city due to a multitude of factors, including cost of living, local economic conditions, and industry presence.
For example, as of April 01, 2025, the average yearly salary of Top Data Scientist in San Francisco, CA is $340,704 and in New York, NY, the average annual salary goes to $316,151. While a Top Data Scientist earns $304,257 per year in Boston, MA.
For those exploring the changing dynamics of Top Data Scientist salaries, Salary.com offers detailed insights through our Job Trending in CA Labor Market analysis. As of April 01, 2025, our research highlights a notable shift in Top Data Scientist compensation over the past six years. For instance, the median salary has moved from $250,444 in 2023 to about $250,974 in 2024 (for a comprehensive analysis of Top Data Scientist salary trends, click here). It's crucial to consider several elements, including geographical location, experience level, industry demand, and economic development, as they play a significant role in influencing salary variations.
Salary.com job board provides millions of Top Data Scientist information for you to search for. Click on search button below to see Top Data Scientist job openings or enter a new job title here.
Here are companies hiring for Top Data Scientist and their salaries, click below for more details.
| Core Compensation | ||||
| Core Compensation | Median | % of Total | ||
| Base Salary | $272,803 | 76.1% | ||
| Bonus | $0 | 0.0% | ||
| Value of Benefits | ||||
| Core Compensation | Median | % of Total | ||
| Social Security | $14,409 | 4.0% | ||
| 401K/403B | $10,500 | 2.9% | ||
| Disability | $5,456 | 1.5% | ||
| Healthcare | $8,352 | 2.3% | ||
| Pension | $13,500 | 3.8% | ||
| Time Off | $33,576 | 9.4% | ||
| Total Compensation | $358,596 | 100% | ||
Develops and executes the data science vision, strategy, and capacity to support organizational long-term, short-term, and mission-critical goals. Provides the organization with data insights, analytics, and tools to achieve business goals, foster innovation, and promote data-driven decision-making. Engages stakeholders and champions the design and development of data science initiatives. Researches and incorporates emerging technologies and methods to continuously improve analytic capabilities and enhance capacity to provide valuable results. Builds team capability with mentoring, coaching, and professional development. Possesses a deep and broad knowledge of data science, analytical concepts and methods, and business operations. Typically requires a master's degree in computer science, mathematics, engineering or equivalent. Typically reports to top management. Manages a business unit, division, or corporate function with major organizational impact. Establishes overall direction and strategic initiatives for the given major function or line of business. Has acquired the business acumen and leadership experience to become a top function or division head.
Specify the abilities and skills that a person needs in order to carry out the specified job duties. Each competency has five to ten behavioral assertions that can be observed, each with a corresponding performance level (from one to five) that is required for a particular job.
Analysis: Analysis is the process of considering something carefully or using statistical methods in order to understand it or explain it.
Data Analysis: Data analysis is a process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making. Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, and is used in different business, science, and social science domains. In today's business world, data analysis plays a role in making decisions more scientific and helping businesses operate more effectively. Data mining is a particular data analysis technique that focuses on modeling and knowledge discovery for predictive rather than purely descriptive purposes, while business intelligence covers data analysis that relies heavily on aggregation, focusing mainly on business information. In statistical applications, data analysis can be divided into descriptive statistics, exploratory data analysis (EDA), and confirmatory data analysis (CDA). EDA focuses on discovering new features in the data while CDA focuses on confirming or falsifying existing hypotheses. Predictive analytics focuses on application of statistical models for predictive forecasting or classification, while text analytics applies statistical, linguistic, and structural techniques to extract and classify information from textual sources, a species of unstructured data. All of the above are varieties of data analysis.
Tableau: Using business intelligence software to perform data analysis, data visualization, and the BI process of an organization.
