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Statistical data analysts use a variety of tools and methodologies to gather, analyze, and model data to support decision-making within organizations and corporations. This role requires a high level of analytical thinking, extensive familiarity with statistical methodologies and principles, and expertise with computer software and programming languages used in data mining, validation, and analytics.
This role has grown significantly as companies and organizations increasingly rely on complex data to drive decision-making. Because of the complexity and necessity of working with data to grow and sustain organizations, statistical data analysts can work in a variety of industries.
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Statistical Data Analyst Duties and Responsibilities
While statistical data analysts can work in a variety of settings, most share several core responsibilities:
Gather and Validate Data
One of the primary responsibilities of a statistical data analyst is to collect and validate data related to a specific project. A statistical data analyst typically uses a data mining program to extract raw data for analysis, performing validation and organization before conducting analysis. The type of data can greatly depend on the project.
Analyze and Interpret Data Sets
Data analysis and interpretation is central to the statistical data analyst's role. They use SAS and R programs and methodologies to identify patterns within data and to process raw data into usable information for executives and other decision-makers.
Develop and Maintain Databases
Statistical data analysts develop and maintain databases for use in future projects. This part of the job requires extensive familiarity with data management, structures, and security. The statistical data analyst may also enter metadata for easier data analysis and sorting, which allows them to tag data based on its source, subject matter, or other notable characteristics.
Model Data and Analytics
In addition to gathering and analyzing data, statistical data analysts develop complex data models using specialized software. These models may illustrate findings from current data, provide forecasts or predictive information based on statistical analysis, or present several different models depending on factors that may affect the data.
Prepare and Present Reports
Often, statistical data analysts prepare reports on their findings and present them to executives and other organizational decision-makers. These reports typically explain the processes of data gathering and analysis, present several different data models and permutations, and provide the analyst's findings. The executive then uses these reports to make informed decisions regarding operations or personnel.
Improve Process Efficiency
Statistical data analysts constantly seek ways to improve process efficiency and effectiveness. This often involves some degree of coding or programming, with analysts developing algorithms and methods to better process data and eliminate redundancies or gaps in the data mining process.
Statistical Data Analyst Skills and Qualifications
Statistical data analysts gather and assess large, complex sets of data to derive insights and support organizational decision-making. Most workers in this role have at least a bachelor's degree and the following skills:
Analytical thinking – statistical data analysts spend much of their time gathering, validating, and analyzing data, so they need rigorous analytical skills and the ability to apply these skills to complicated problems
Data modeling – effective data modeling is central to this role, as statistical data analysts need to develop accurate models based on their findings and a variety of inputs to help guide decision-making
Statistics expertise – statistical data analysts should also possess extensive knowledge of statistics, including methods and processes for determining possible outcomes and considering multiple factors and their effects
Critical thinking – this role also requires excellent critical thinking skills, particularly when the statistical data analyst needs to assess the quality of data and perform validation
Attention to detail – accuracy is key to this role, so statistical data analysts should have a high level of attention to detail to ensure that their analysis and models are thorough and correct
Communication skills – verbal and written communication are essential in this role, since statistical data analysts need to prepare and present reports on their findings to management and executives
Tools of the Trade
Statistical data analysts tend to work in office settings, so they should be familiar with standard office software and equipment in addition to the following:
Data mining, analysis, and visualization tools (SAS and R-based)
Statistical Data Analyst Education and Training
Statistical data analysts typically have at least a bachelor's degree in a closely related field, such as statistics or mathematics. Additionally, workers in this role tend to have proficiency with software and programming languages related to their work, such as SAS and R, which some bachelor's degree programs incorporate into their syllabi. There are few opportunities for on-the-job training in this role, although most statistical data analysts gain further expertise and develop improved strategies and tools while on the job.
Statistical Data Analyst Salary and Outlook
The Bureau of Labor Statistics (BLS) categorizes statistical data analysts as operations research analysts. The BLS found that workers in this field earn a median annual salary of $81,390. The highest-paid 10 percent of workers in this role earn more than $134,470 per year, while the lowest-paid 10 percent earn less than $45,270 annually.
The BLS expects this field to grow at a very rapid pace of 27 percent through 2026, as companies increasingly rely on complex data to drive decision-making.
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American Statistical Association
ASA is a professional organization for data analysts and statisticians, providing career development and educational resources, annual conferences to connect with others in the field, and industry publications
An Introduction to Statistical Methods and Data Analysis
this book provides a comprehensive introduction to data gathering and validation, analysis and modeling, and other tools and methods used by statistical data analysts
Data Science Association
statistical data analysts can join DSA to access professional resources and publications related to the field of data analysis, and to attend events and conferences to stay informed and connected
R for Data Science
read this book to learn the fundamentals of R, a programming language that provides data analysts with a suite of tools and resources to conduct data mining, analysis, and visualization