Applied Scientist vs. Data Science Consultant

Applied Scientist vs Data Science Consultant: A Comprehensive Comparison

Table of contents

Data science is a rapidly growing field, with numerous job opportunities and career paths. Two of the most popular job titles in this space are Applied Scientist and Data Science Consultant. While both roles require a strong background in data science, they differ in their responsibilities, required skills, and industries they serve. In this article, we will explore the similarities and differences between these two job titles, and provide practical tips for getting started in these careers.

What is an Applied Scientist?

An Applied Scientist is a data scientist who applies machine learning and statistical techniques to solve real-world problems. They work in a variety of industries, including healthcare, finance, and E-commerce, to name a few. Applied Scientists are responsible for designing and implementing machine learning models, analyzing data, and communicating their findings to stakeholders. They often work in interdisciplinary teams with software engineers, product managers, and business analysts.

What is a Data Science Consultant?

A Data Science Consultant is a data scientist who works with clients to solve complex data-related problems. They work in Consulting firms, helping clients in various industries to improve their business processes, develop data strategies, and implement data-driven solutions. Data Science Consultants are responsible for analyzing large datasets, developing predictive models, and presenting their findings to clients. They work in a variety of domains, including healthcare, finance, and marketing.

Responsibilities

The responsibilities of Applied Scientists and Data Science Consultants differ based on their job titles. Applied Scientists are responsible for designing and implementing Machine Learning models, analyzing data, and communicating their findings to stakeholders. They work on specific projects within their organization, and collaborate with other teams to develop solutions. Data Science Consultants, on the other hand, work with clients to solve complex data-related problems. They analyze large datasets, develop predictive models, and present their findings to clients. They work on a variety of projects across different industries and domains.

Required Skills

Both Applied Scientists and Data Science Consultants require a strong background in data science, including Statistics, machine learning, and programming. They also need to have excellent communication skills, as they need to be able to explain complex technical concepts to non-technical stakeholders. However, there are some differences in the skills required for each role.

Applied Scientists need to have a strong foundation in mathematics, statistics, and Computer Science. They need to be proficient in programming languages such as Python and R, and have experience with machine learning frameworks such as TensorFlow and PyTorch. They also need to be familiar with data visualization tools such as Tableau and Power BI.

Data Science Consultants, on the other hand, need to have excellent problem-solving skills and the ability to work well with clients. They need to be able to understand the client's business requirements and develop solutions that meet their needs. They also need to have experience with project management and be able to work on multiple projects simultaneously. In addition to technical skills, they need to have strong communication and presentation skills.

Educational Background

The educational background required for Applied Scientists and Data Science Consultants is similar. Both roles require a strong foundation in data science, including statistics, machine learning, and programming. A bachelor's degree in computer science, Mathematics, or a related field is typically required for both roles. However, some employers may prefer candidates with a master's degree or Ph.D. in a related field.

Tools and Software Used

The tools and software used by Applied Scientists and Data Science Consultants also overlap to some extent. Both roles require proficiency in programming languages such as Python and R, as well as machine learning frameworks such as TensorFlow and PyTorch. They also need to be familiar with Data visualization tools such as Tableau and Power BI.

However, Applied Scientists may also use specialized tools and software for their work, depending on their domain. For example, those working in the healthcare industry may use electronic health record systems, while those working in Finance may use trading platforms and financial data sources.

Common Industries

Applied Scientists and Data Science Consultants work in a variety of industries, including healthcare, finance, e-commerce, and marketing. However, there are some differences in the industries they serve.

Applied Scientists typically work in Research and development teams within an organization, such as a healthcare provider, financial institution, or tech company. They focus on developing machine learning models and data-driven solutions that improve the organization's products or services.

Data Science Consultants, on the other hand, work in consulting firms and serve clients across different industries. They focus on solving complex data-related problems for their clients, such as improving supply chain management, optimizing marketing campaigns, or developing predictive models for risk analysis.

Outlooks

Both Applied Scientists and Data Science Consultants have strong job outlooks, with high demand and competitive salaries. According to the Bureau of Labor Statistics, the employment of computer and information research scientists, which includes Applied Scientists, is projected to grow 15% from 2019 to 2029, much faster than the average for all occupations. Similarly, the employment of management analysts, which includes Data Science Consultants, is projected to grow 11% from 2019 to 2029.

Practical Tips for Getting Started

If you are interested in pursuing a career as an Applied Scientist or Data Science Consultant, here are some practical tips to get started:

• Build a strong foundation in data science, including statistics, machine learning, and programming.
• Gain experience with relevant tools and software, such as Python, R, TensorFlow, and Tableau.
• Develop strong communication and presentation skills, as you will need to explain complex technical concepts to non-technical stakeholders.
• Consider pursuing a master's degree or Ph.D. in a related field to enhance your skills and knowledge.
• Look for internships or entry-level positions in relevant industries to gain practical experience.

Conclusion

Applied Scientists and Data Science Consultants are both important roles in the data science industry, with similar foundational skills but different responsibilities and industries they serve. By understanding the differences between these roles and their requirements, you can make an informed decision about which career path is right for you. With the right skills and experience, you can build a successful career in the growing field of data science.