Applied Scientist vs. BI Analyst

Applied Scientist vs. BI Analyst: A Comprehensive Comparison

5 min read · Dec. 6, 2023

Career

Definitions
Responsibilities
Required Skills
Educational Backgrounds
Tools and Software Used
Common Industries
Outlooks
Practical Tips for Getting Started
Conclusion

As the world becomes increasingly data-driven, the demand for professionals who can make sense of large datasets and extract insights from them has grown exponentially. Two popular roles in this field are Applied Scientist and BI Analyst. While both roles involve working with data, they differ in their focus, responsibilities, required skills, educational backgrounds, tools and software used, common industries, outlooks, and practical tips for getting started in these careers. In this article, we will explore these differences in detail.

Definitions

An Applied Scientist is a professional who applies scientific principles and techniques to solve real-world problems. They use Data analysis, Machine Learning, and Statistical modeling to create predictive models, develop algorithms, and build systems that can automate decision-making processes.

A BI Analyst, on the other hand, is a professional who uses data analysis and visualization tools to create reports, dashboards, and other Business Intelligence solutions that help organizations make informed decisions. They work with business stakeholders to identify key performance indicators (KPIs) and create metrics that measure the success of business processes.

Responsibilities

The responsibilities of an Applied Scientist and a BI Analyst differ significantly.

An Applied Scientist is responsible for:

Collecting and cleaning large datasets
Developing and Testing machine learning models
Building and deploying predictive models
Analyzing data to identify patterns and trends
Communicating insights to stakeholders
Continuously improving models based on feedback and new data

A BI Analyst, on the other hand, is responsible for:

Gathering data from multiple sources
Cleaning and transforming data into a usable format
Creating reports, dashboards, and other visualizations
Identifying KPIs and creating metrics
Analyzing data to identify trends and patterns
Communicating insights to stakeholders
Collaborating with other teams to improve Data quality and accuracy

Required Skills

Both Applied Scientists and BI Analysts need to have strong analytical skills, attention to detail, and the ability to work with large datasets. However, the specific skills required for each role differ significantly.

Applied Scientists need to have:

Strong programming skills in languages such as Python, R, and Java
Knowledge of Machine Learning algorithms and techniques
Experience with Data visualization tools such as Tableau and Power BI
Understanding of Statistical modeling and analysis
Strong problem-solving and critical thinking skills
Excellent communication and presentation skills

BI Analysts need to have:

Strong proficiency in SQL and data visualization tools such as Tableau and Power BI
Knowledge of Data Warehousing and ETL processes
Understanding of business processes and KPIs
Ability to translate technical data into business insights
Strong problem-solving and critical thinking skills
Excellent communication and presentation skills

Educational Backgrounds

Applied Scientists typically have a background in Computer Science, Mathematics, Statistics, or a related field. They often have advanced degrees such as a Master's or Ph.D. in a relevant field.

BI Analysts typically have a background in business, Finance, Economics, or a related field. They often have a bachelor's degree in a relevant field, although some may have advanced degrees.

Tools and Software Used

Applied Scientists and BI Analysts use different tools and software to perform their jobs.

Applied Scientists typically use:

Programming languages such as Python, R, and Java
Machine learning libraries such as TensorFlow, PyTorch, and Scikit-learn
Data visualization tools such as Tableau, Power BI, and Matplotlib
Cloud computing platforms such as AWS, Azure, and Google Cloud
Statistical analysis tools such as SAS and SPSS

BI Analysts typically use:

SQL and relational databases such as MySQL, SQL Server, and Oracle
Data visualization tools such as Tableau, Power BI, and QlikView
Business Intelligence tools such as SAP BusinessObjects and IBM Cognos
ETL tools such as Informatica and Talend

Common Industries

Applied Scientists and BI Analysts work in different industries, although there is some overlap.

Applied Scientists often work in:

Technology companies such as Google, Amazon, and Microsoft
Healthcare companies such as Pfizer and Johnson & Johnson
Financial services companies such as JPMorgan Chase and Goldman Sachs
Retail companies such as Walmart and Target
Consulting firms such as McKinsey and Accenture

BI Analysts often work in:

Retail companies such as Walmart and Target
Financial services companies such as JPMorgan Chase and Goldman Sachs
Healthcare companies such as Pfizer and Johnson & Johnson
Government agencies such as the Department of Defense and the IRS
Consulting firms such as Deloitte and PwC

Outlooks

Both Applied Scientists and BI Analysts have strong job outlooks, with high demand and good salaries.

According to the Bureau of Labor Statistics, the median annual salary for computer and information Research scientists (which includes Applied Scientists) was $126,830 in May 2020. The job outlook is also strong, with a projected growth rate of 15% from 2019 to 2029.

According to Glassdoor, the average annual salary for BI Analysts in the United States is $76,000. The job outlook is also strong, with a projected growth rate of 11% from 2019 to 2029.