1. What is the average salary of a Clinical Biostatistics Director?
The average annual salary of Clinical Biostatistics Director is $203,155.
In case you are finding an easy salary calculator,
the average hourly pay of Clinical Biostatistics Director is $98;
the average weekly pay of Clinical Biostatistics Director is $3,907;
the average monthly pay of Clinical Biostatistics Director is $16,930.
2. Where can a Clinical Biostatistics Director earn the most?
A Clinical Biostatistics Director'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 Clinical Biostatistics Director earns the most in San Jose, CA, where the annual salary of a Clinical Biostatistics Director is $254,960.
3. What is the highest pay for Clinical Biostatistics Director?
The highest pay for Clinical Biostatistics Director is $256,074.
4. What is the lowest pay for Clinical Biostatistics Director?
The lowest pay for Clinical Biostatistics Director is $160,153.
5. What are the responsibilities of Clinical Biostatistics Director?
Clinical Biostatistics Director directs an organization's clinical biostatistics or health informatics department. Oversees the analysis, management and performance of health information data to aid patient care. Being a Clinical Biostatistics Director monitors latest software and technology to keep processes up-to-date and efficient. Communicates with other departments and team members to identify new sources of data, ensure data is used effectively, and establish new initiatives. Additionally, Clinical Biostatistics Director requires a master's degree. Typically reports to senior management. The Clinical Biostatistics Director manages a departmental sub-function within a broader departmental function. Creates functional strategies and specific objectives for the sub-function and develops budgets/policies/procedures to support the functional infrastructure. To be a Clinical Biostatistics Director typically requires 5+ years of managerial experience. Deep knowledge of the managed sub-function and solid knowledge of the overall departmental function.
6. What are the skills of Clinical Biostatistics Director
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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Data Management: Data Management comprises all disciplines related to managing data as a valuable resource. The concept of data management arose in the 1980s as technology moved from sequential processing (first cards, then tape) to random access storage. Since it was now possible to store a discreet fact and quickly access it using random access disk technology, those suggesting that data management was more important than business process management used arguments such as "a customer's home address is stored in 75 (or some other large number) places in our computer systems." However, during this period, random access processing was not competitively fast, so those suggesting "process management" was more important than "data management" used batch processing time as their primary argument. As software applications evolved into real-time, interactive usage, it became obvious that both management processes were important. If the data was not well defined, the data would be mis-used in applications. If the process wasn't well defined, it was impossible to meet user needs.
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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.
