How much does a Data Scientist II make in Saint George, UT? The average Data Scientist II salary in Saint George, UT is $95,715 as of August 27, 2024, but the range typically falls between $85,459 and $105,637. Salary ranges can vary widely depending on many important factors, including education, certifications, additional skills, the number of years you have spent in your profession. With more online, real-time compensation data than any other website, Salary.com helps you determine your exact pay target.
Percentile | Salary | Location | Last Updated |
10th Percentile Data Scientist II Salary | $76,121 | Saint George,UT | August 27, 2024 |
25th Percentile Data Scientist II Salary | $85,459 | Saint George,UT | August 27, 2024 |
50th Percentile Data Scientist II Salary | $95,715 | Saint George,UT | August 27, 2024 |
75th Percentile Data Scientist II Salary | $105,637 | Saint George,UT | August 27, 2024 |
90th Percentile Data Scientist II Salary | $114,670 | Saint George,UT | August 27, 2024 |
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.
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 |
---|---|---|
Collaboration
|
$98,586 |
3%
|
Insight
|
$97,629 |
2%
|
Algorithms
|
$97,629 |
2%
|
Leadership
|
$97,629 |
2%
|
Big Data
|
$96,672 |
1%
|
Machine Learning
|
$96,672 |
1%
|
What Should I Pay?
Data Scientist II identifies trends, patterns, and anomalies found in big data sets by performing extensive data analysis to develop insights. Performs data mining, cleaning, and aggregation processes to prepare data, implement data models, conduct analysis, and develop databases. Being a Data Scientist II interprets results from multiple structured and unstructured data sources using programming, statistical, and analytical techniques and tools. Collaborates with teams to understand each data analysis projects' underlying purpose, focus, and objectives. Additionally, Data Scientist II designs, develops, and implements the most valuable data-driven solutions for the organization. Typically requires a master's degree in computer science, mathematics, engineering or equivalent. Typically reports to a manager. The Data Scientist II occasionally directed in several aspects of the work. Gaining exposure to some of the complex tasks within the job function. To be a Data Scientist II typically requires 2 -4 years of related experience. (Copyright 2024 Salary.com)... View full job description
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A career path is a sequence of jobs that leads to your short- and long-term career goals. Some follow a linear career path within one field, while others change fields periodically to achieve career or personal goals.
For Data Scientist II, the upper level is Data Scientist III and then progresses to Data Scientist IV.
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Data Scientist II salary varies from city to city. Compared with national average salary of Data Scientist II, the highest Data Scientist II salary is in San Francisco, CA, where the Data Scientist II salary is 25.0% above. The lowest Data Scientist II salary is in Miami, FL, where the Data Scientist II salary is 3.5% lower than national average salary.
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Job Title | Experience | EDUCATION | Salary Compared to This Job |
---|---|---|---|
Job Title Data Analyst II | Experience 2 - 4 | EducationBachelors | Salary Compared to This Job |
Job Title Data Architect II | Experience 2 - 4 | EducationBachelors | Salary Compared to This Job |
Job Title Data Center Administrator II | Experience 2 - 4 | EducationBachelors | Salary Compared to This Job |
Job Title Data Processing Specialist II | Experience 1 - 3 | EducationHigh School | Salary Compared to This Job |
Job Title Data Scientist I | Experience 0 - 2 | EducationMasters | Salary Compared to This Job |
Jobs with different levels of education may pay very differently. Check the Data Scientist II salary of your education level.
Data Scientist II salary varies from country to country. There are several factors that mainly impact the Data Scientist II salary, including cost of living, economic conditions, market rates and legal differences. Click below to Data Scientist II salary of the other country.
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About Saint George, Utah St. George is a city in and the county seat of Washington County, Utah, United States. Located in the southwestern part of the state on the Arizona bo....More
Saint George, Utah area prices were up 2.5% from a year ago View the Cost of Living in Saint George, Utah
Data Scientist II Salary in popular cities: Salt Lake City, Provo, West Jordan
Skills associated with Data Scientist II: Data Cleansing, Data Science, Big Data, Data Architecture ...More
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