1. What is the average salary of a Research and Development Associate I?
The average annual salary of Research and Development Associate I is $65,446.
In case you are finding an easy salary calculator,
the average hourly pay of Research and Development Associate I is $31;
the average weekly pay of Research and Development Associate I is $1,259;
the average monthly pay of Research and Development Associate I is $5,454.
2. Where can a Research and Development Associate I earn the most?
A Research and Development Associate 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, a Research and Development Associate I earns the most in San Jose, CA, where the annual salary of a Research and Development Associate I is $82,547.
3. What is the highest pay for Research and Development Associate I?
The highest pay for Research and Development Associate I is $81,937.
4. What is the lowest pay for Research and Development Associate I?
The lowest pay for Research and Development Associate I is $51,204.
5. What are the responsibilities of Research and Development Associate I?
Participates in research and development activities. Utilizes established mathematical and scientific techniques to compile and analyze data. Writes technical reports detailing procedures, outcomes, and observations. Requires a bachelor's degree. Typically reports to a supervisor or manager. Works on projects/matters of limited complexity in a support role. Work is closely managed. Typically requires 0-2 years of related experience.
6. What are the skills of Research and Development Associate 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.
2.)
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.
3.)
Immunology: Immunology is the study of the immune system and is a very important branch of the medical and biological sciences. The immune system protects us from infection through various lines of defence.