1. What is the average salary of an IRA Specialist?
The average annual salary of IRA Specialist is $55,838.
In case you are finding an easy salary calculator,
the average hourly pay of IRA Specialist is $27;
the average weekly pay of IRA Specialist is $1,074;
the average monthly pay of IRA Specialist is $4,653.
2. Where can an IRA Specialist earn the most?
An IRA Specialist'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 IRA Specialist earns the most in San Jose, CA, where the annual salary of an IRA Specialist is $70,076.
3. What is the highest pay for IRA Specialist?
The highest pay for IRA Specialist is $68,517.
4. What is the lowest pay for IRA Specialist?
The lowest pay for IRA Specialist is $43,942.
5. What are the responsibilities of IRA Specialist?
IRA Specialist develops IRA rate sheets and prepares transfers, distributions, rollovers, conversions, death claims, and closures in accordance with government regulations and bank policies. Maintains retirement records and is responsible for current and proper financial statements and reports. Being an IRA Specialist utilizes database or system to process transactions and retrieve information. May require a bachelor's degree. Additionally, IRA Specialist typically reports to a supervisor or manager. The IRA Specialist works on projects/matters of limited complexity in a support role. Work is closely managed. To be an IRA Specialist typically requires 0-2 years of related experience.
6. What are the skills of IRA Specialist
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.)
Problem Solving: Analyzing and identifying the root cause of problems and applying critical thinking skills to solve problems.
2.)
SQL: Structured Query Language) is a domain-specific language used in programming and designed for managing data held in a relational database management system (RDBMS), or for stream processing in a relational data stream management system (RDSMS).
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Data Analytics: 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.