1. What is the average salary of an Economic Data Analyst I?
The average annual salary of Economic Data Analyst I is $96,600.
In case you are finding an easy salary calculator,
the average hourly pay of Economic Data Analyst I is $46;
the average weekly pay of Economic Data Analyst I is $1,858;
the average monthly pay of Economic Data Analyst I is $8,050.
2. Where can an Economic Data Analyst I earn the most?
An Economic Data Analyst I'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, an Economic Data Analyst I earns the most in San Jose, CA, where the annual salary of an Economic Data Analyst I is $121,200.
3. What is the highest pay for Economic Data Analyst I?
The highest pay for Economic Data Analyst I is $123,155.
4. What is the lowest pay for Economic Data Analyst I?
The lowest pay for Economic Data Analyst I is $66,415.
5. What are the responsibilities of Economic Data Analyst I?
The Economic Data Analyst I organizes data into report format and arranges graphic illustrations of research findings. Conducts research and analysis on economic data/trends and provides interpretation. Being an Economic Data Analyst I prepares reports for management indicating business implications. Assists in analyzing economic conditions by professional knowledge and application. In addition, Economic Data Analyst I requires a bachelor's degree. Typically reports to a Supervisor or Manager. Being an Economic Data Analyst I gains exposure to some of the complex tasks within the job function. Occasionally directed in several aspects of the work. Working as an Economic Data Analyst I typically requires 2 to 4 years of related experience.
6. What are the skills of Economic Data Analyst I
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.
1.)
Analysis: Analysis is the process of considering something carefully or using statistical methods in order to understand it or explain it.
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Forecasting: Forecasting is the process of making predictions of the future based on past and present data and most commonly by analysis of trends. A commonplace example might be estimation of some variable of interest at some specified future date. Prediction is a similar, but more general term. Both might refer to formal statistical methods employing time series, cross-sectional or longitudinal data, or alternatively to less formal judgmental methods. Usage can differ between areas of application: for example, in hydrology the terms "forecast" and "forecasting" are sometimes reserved for estimates of values at certain specific future times, while the term "prediction" is used for more general estimates, such as the number of times floods will occur over a long period. Risk and uncertainty are central to forecasting and prediction; it is generally considered good practice to indicate the degree of uncertainty attaching to forecasts. In any case, the data must be up to date in order for the forecast to be as accurate as possible. In some cases the data used to predict the variable of interest is itself forecasted.
3.)
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.
