Applied Scientist vs. Business Intelligence Data Analyst

Applied Scientist vs Business Intelligence Data Analyst: A Comprehensive Comparison

Table of contents

In the tech industry, there are numerous career paths available for individuals with a passion for data science and analytics. Two of the most popular roles are Applied Scientist and Business Intelligence Data Analyst. While both roles involve working with data, they have distinct differences in their responsibilities, required skills, educational backgrounds, tools and software used, common industries, outlooks, and practical tips for getting started in these careers. This article will provide a detailed comparison of these two roles.

Definitions

An Applied Scientist is a professional who applies scientific principles to solve real-world problems. They use advanced mathematical and statistical models to develop and improve products and services. They work on a wide range of projects, including developing algorithms for Machine Learning, creating predictive models, and analyzing complex data to identify patterns and trends.

On the other hand, a Business Intelligence Data Analyst is a professional who analyzes and interprets data to help organizations make informed decisions. They work with large datasets to identify trends, patterns, and insights that can be used to improve business performance. They also design and develop dashboards, reports, and visualizations to communicate data insights to stakeholders.

Responsibilities

The responsibilities of an Applied Scientist and a Business Intelligence Data Analyst are different. An Applied Scientist is responsible for developing and improving products and services using advanced mathematical and statistical models. They work on a wide range of projects, including developing algorithms for Machine Learning, creating predictive models, and analyzing complex data to identify patterns and trends.

On the other hand, a Business Intelligence Data Analyst is responsible for analyzing and interpreting data to help organizations make informed decisions. They work with large datasets to identify trends, patterns, and insights that can be used to improve business performance. They also design and develop dashboards, reports, and visualizations to communicate data insights to stakeholders.

Required Skills

The required skills for an Applied Scientist and a Business Intelligence Data Analyst are different. An Applied Scientist must have a strong foundation in Mathematics, Statistics, and Computer Science. They must also have programming skills in languages such as Python, R, and Java. Additionally, they must have experience working with machine learning algorithms and Data analysis tools.

On the other hand, a Business Intelligence Data Analyst must have strong analytical and problem-solving skills. They must be able to work with large datasets and have experience using data analysis tools such as SQL, Excel, and Tableau. They must also have strong communication skills to effectively communicate data insights to stakeholders.

Educational Backgrounds

The educational backgrounds for an Applied Scientist and a Business Intelligence Data Analyst are different. An Applied Scientist typically has a Ph.D. in a field such as Computer Science, mathematics, or statistics. They may also have a Master's degree in a related field. Additionally, they may have completed specialized training in machine learning and data analysis.

On the other hand, a Business Intelligence Data Analyst typically has a Bachelor's degree in a field such as computer science, mathematics, or statistics. They may also have completed specialized training in Data analysis and visualization.

Tools and Software Used

The tools and software used by an Applied Scientist and a Business Intelligence Data Analyst are different. An Applied Scientist typically uses programming languages such as Python, R, and Java. They also use machine learning libraries such as TensorFlow, PyTorch, and Scikit-learn. Additionally, they may use data analysis tools such as Jupyter Notebook, Matlab, and SAS.

On the other hand, a Business Intelligence Data Analyst typically uses data analysis tools such as SQL, Excel, and Tableau. They also use visualization tools such as Power BI and QlikView.

Common Industries

The industries where Applied Scientists and Business Intelligence Data Analysts work are different. Applied Scientists typically work in industries such as tech, healthcare, Finance, and retail. They may work for companies such as Amazon, Google, Microsoft, and IBM.

On the other hand, Business Intelligence Data Analysts typically work in industries such as Finance, healthcare, retail, and marketing. They may work for companies such as Goldman Sachs, JPMorgan Chase, and McKinsey & Company.

Outlooks

The outlooks for Applied Scientists and Business Intelligence Data Analysts are positive. According to the Bureau of Labor Statistics, employment of computer and information Research scientists, which includes Applied Scientists, is projected to grow 15 percent from 2019 to 2029, much faster than the average for all occupations. Additionally, according to Glassdoor, the average salary for an Applied Scientist is $117,000 per year.

Similarly, according to the Bureau of Labor Statistics, employment of management analysts, which includes Business Intelligence Data Analysts, is projected to grow 11 percent from 2019 to 2029, much faster than the average for all occupations. Additionally, according to Glassdoor, the average salary for a Business Intelligence Data Analyst is $75,000 per year.

Practical Tips for Getting Started

If you are interested in becoming an Applied Scientist, you should consider pursuing a Ph.D. in a field such as computer science, Mathematics, or statistics. Additionally, you should gain experience working with machine learning algorithms and data analysis tools. You can also participate in online courses and certifications to enhance your skills.

If you are interested in becoming a Business Intelligence Data Analyst, you should consider pursuing a Bachelor's degree in a field such as computer science, mathematics, or statistics. Additionally, you should gain experience working with data analysis tools such as SQL, Excel, and Tableau. You can also participate in online courses and certifications to enhance your skills.

Conclusion

In conclusion, Applied Scientists and Business Intelligence Data Analysts are both valuable professionals in the tech industry. While they have different responsibilities, required skills, educational backgrounds, tools and software used, common industries, and outlooks, they both work with data to solve problems and make informed decisions. If you have a passion for data science and analytics, both of these roles are worth considering.