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 February 01, 2025, the average annual salary for a Top Data Scientist in the United States is $281,984. According to Salary.com, salaries can range from a low of $231,811 to a high of $345,734, with most professionals earning between $255,722 and $315,353.
| Annual Salary |
Monthly Pay |
Weekly Pay |
Hourly Wage |
|
| 75th Percentile | $315,353 | $26,279 | $6,064 | $152 |
| Average | $281,984 | $23,499 | $5,423 | $136 |
| 25th Percentile | $255,722 | $21,310 | $4,918 | $123 |
An entry-level Top Data Scientist with less than 1 year of experience earns about $263,164. With 1-2 years of experience, the average salary increases to $265,492. For 2-4 years of experience, the pay typically rises to $268,594. Senior-level professionals with 5-8 years of experience earn around $273,249, and those with over 8 years of experience can expect an average of $279,067.
| Levels | Salary |
|---|---|
| Entry Level Top Data Scientist | $263,164 |
| Intermediate Level Top Data Scientist | $265,492 |
| Senior Level Top Data Scientist | $268,594 |
| Specialist Level Top Data Scientist | $273,249 |
| Expert Level Top Data Scientist | $279,067 |
| Entry Level | 7% |
| Mid Level | 6% |
| Senior Level | 5% |
| Top Level | 3% |
| Experienced | 1% |
Salaries in the United States differ widely between states due to factors like cost of living, local economies, and industry presence.
What Am I Worth?
Salaries in the United States can vary greatly between cities due to factors like cost of living, local economies, and industry presence.
As of February 01, 2025, our research reveals a significant shift in Top Data Scientist compensation over the past six years. For example, the median salary increased from $250,444 in 2023 to approximately $250,974 in 2024. (For a detailed analysis of Top Data Scientist salary trends, click here.)
Key factors like location, experience, industry demand, and economic growth significantly influence salary variations, making them important to consider.
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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 | $281,984 | 63.3% | ||
| Bonus | $65,762 | 14.8% | ||
| Value of Benefits | ||||
| Core Compensation | Median | % of Total | ||
| Social Security | $15,496 | 3.5% | ||
| 401K/403B | $10,500 | 2.4% | ||
| Disability | $6,955 | 1.6% | ||
| Healthcare | $8,352 | 1.9% | ||
| Pension | $13,500 | 3.0% | ||
| Time Off | $42,799 | 9.6% | ||
| Total Compensation | $445,347 | 100% | ||
The average annual salary of Top Data Scientist is $281,984. In case you are finding an easy salary calculator, the average hourly pay of Top Data Scientist is $136; the average weekly pay of Top Data Scientist is $5,423; the average monthly pay of Top Data Scientist is $23,499.
A Top Data Scientist's earning potential can vary widely depending on several factors, including location, industry, experience, education, and the specific employer. According to the latest salary data by Salary.com, a Top Data Scientist earns the most in San Jose, CA, where the annual salary of a Top Data Scientist is $353,890.
The highest pay for Top Data Scientist is $345,734.
The lowest pay for Top Data Scientist is $231,811.
Top Data Scientist 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. Being a Top Data Scientist 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. Additionally, Top Data Scientist 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. The Top Data Scientist 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.
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