As of December 01, 2024, the average annual pay of Data Scientist III in Ames, IA is $116,623. While Salary.com is seeing that Data Scientist III salary in Ames, IA can go up to $140,877 or down to $94,977, but most earn between $105,293 and $129,318. Salary.com shows the average base salary (core compensation), as well as the average total cash compensation for the job of Data Scientist III in the United States.
| Annual Salary |
Monthly Pay |
Weekly Pay |
Hourly Wage |
|
| 75th Percentile | $134,566 | $11,214 | $2,588 | $65 |
| Average | $121,356 | $10,113 | $2,334 | $58 |
| 25th Percentile | $109,566 | $9,130 | $2,107 | $53 |
An entry-level Data Scientist III with under 1 year experience makes about $116,029. With less than 2 years of experience, a mid-level Data Scientist III makes around $116,029. After 2-4 years, the Data Scientist III pay rises to about $116,029. Those senior Data Scientist III with 5-8 years of experience earn roughly $116,029, and those Data Scientist III having 8 years or more experience are expected to earn about $116,029 on average.
| Levels | Salary |
|---|---|
| Entry Level Data Scientist III | $116,029 |
| Intermediate Level Data Scientist III | $116,029 |
| Senior Level Data Scientist III | $116,029 |
| Specialist Level Data Scientist III | $116,029 |
| Expert Level Data Scientist III | $116,029 |
| Entry Level | 4% |
| Mid Level | 4% |
| Senior Level | 4% |
| Top Level | 4% |
| Experienced | 4% |
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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.
Computer Science: Computer science is the study of computation, automation, and information. Computer science spans theoretical disciplines (such as algorithms, theory of computation, information theory, and automation) to practical disciplines.
Big Data: Big data is a field that treats ways to analyze, systematically extract information from, or otherwise deal with data sets that are too large or complex to be dealt with by traditional data-processing application software. Data with many cases (rows) offer greater statistical power, while data with higher complexity (more attributes or columns) may lead to a higher false discovery rate. Big data challenges include capturing data, data storage, data analysis, search, sharing, transfer, visualization, querying, updating, information privacy and data source. Big data was originally associated with three key concepts: volume, variety, and velocity. Other concepts later attributed to big data are veracity (i.e., how much noise is in the data) and value. Current usage of the term big data tends to refer to the use of predictive analytics, user behavior analytics, or certain other advanced data analytics methods that extract value from data, and seldom to a particular size of data set. "There is little doubt that the quantities of data now available are indeed large, but that's not the most relevant characteristic of this new data ecosystem." Analysis of data sets can find new correlations to "spot business trends, prevent diseases, combat crime and so on." Scientists, business executives, practitioners of medicine, advertising and governments alike regularly meet difficulties with large data-sets in areas including Internet searches, fintech, urban informatics, and business informatics. Scientists encounter limitations in e-Science work, including meteorology, genomics, connectomics, complex physics simulations, biology and environmental research.
| Skill | Salary | Demand |
|---|---|---|
|
Inference
|
$121,288 |
4%
|
|
Commitment
|
$118,956 |
2%
|
|
Big Data
|
$118,956 |
2%
|
|
Collaboration
|
$118,956 |
2%
|
|
Insight
|
$118,956 |
2%
|
|
AWS
|
$118,956 |
2%
|
