Research Scientist vs. Head of Data Science

Research Scientist vs Head of Data Science: A Detailed Comparison

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As the world becomes increasingly data-driven, the roles of Research Scientist and Head of Data Science have become more vital than ever before. While both roles involve working with data, they differ in their responsibilities, required skills, educational backgrounds, and more. In this article, we will provide a detailed comparison of these two roles.

Definitions

A Research Scientist is responsible for conducting research and developing new technologies in their field. In the context of data science, a Research Scientist focuses on developing new algorithms, models, and techniques to improve Data analysis and machine learning. They work on cutting-edge research projects and are often involved in publishing their findings in academic journals.

On the other hand, a Head of Data Science is responsible for leading a team of data scientists and analysts to solve business problems using data. They work closely with other departments to identify areas where data can be leveraged to improve business outcomes. They are also responsible for ensuring that their team is using the latest tools and techniques to extract insights from data.

Responsibilities

The responsibilities of a Research Scientist and Head of Data Science differ significantly. A Research Scientist is focused on developing new technologies and techniques, while a Head of Data Science is focused on solving business problems. Here are some specific responsibilities for each role:

Research Scientist

• Conducting research in their field of expertise
• Developing new algorithms and models for data analysis and Machine Learning
• Writing research papers and presenting findings at academic conferences
• Collaborating with other researchers and engineers

Head of Data Science

• Leading a team of data scientists and analysts
• Collaborating with other departments to identify business problems that can be solved with data
• Creating data-driven strategies to improve business outcomes
• Ensuring that the team is using the latest tools and techniques to extract insights from data

Required Skills

Both roles require a strong set of technical skills, but there are some differences in the specific skills required.

Research Scientist

• Strong understanding of statistics and Mathematics
• Proficiency in programming languages such as Python, R, and Matlab
• Experience with machine learning algorithms and techniques
• Knowledge of Data visualization tools and techniques
• Strong problem-solving skills

Head of Data Science

• Strong leadership and management skills
• Excellent communication skills
• Experience with data analysis and modeling
• Knowledge of data visualization tools and techniques
• Understanding of business strategy and operations

Educational Background

Both roles require a high level of education, but the specific degree requirements differ.

Research Scientist

• PhD in Computer Science, statistics, mathematics, or a related field
• Research experience in academia or industry

Head of Data Science

• Master's or PhD in data science, computer science, statistics, or a related field
• Experience in data analysis and modeling
• Experience in a leadership or management role

Tools and Software Used

Both roles require the use of various tools and software, but the specific tools and software used differ.

Research Scientist

• Programming languages such as Python, R, and MATLAB
• Machine learning libraries such as TensorFlow, PyTorch, and scikit-learn
• Data visualization tools such as Tableau and Matplotlib
• Cloud computing platforms such as AWS and Google Cloud

Head of Data Science

• Data analysis and modeling tools such as Excel, SQL, and R
• Data visualization tools such as Tableau and Power BI
• Project management tools such as Jira and Trello
• Cloud computing platforms such as AWS and Google Cloud

Common Industries

Both roles are in high demand across a wide range of industries.

Research Scientist

• Technology companies
• Research institutions
• Government agencies
• Healthcare and pharmaceutical companies

Head of Data Science

• Technology companies
• Financial services companies
• Retail and E-commerce companies
• Healthcare and pharmaceutical companies

Outlooks

Both roles have a positive outlook in terms of job growth and salary potential.

Research Scientist

According to the Bureau of Labor Statistics, employment of computer and information research scientists is projected to grow 15 percent from 2019 to 2029, much faster than the average for all occupations. The median annual wage for computer and information research scientists was $126,830 in May 2020.

Head of Data Science

According to Glassdoor, the national average salary for a Head of Data Science is $175,000 per year in the United States. The job outlook for data science managers is positive, with a projected growth rate of 11 percent from 2019 to 2029.

Practical Tips for Getting Started

If you are interested in pursuing a career as a Research Scientist or Head of Data Science, here are some practical tips to get started:

Research Scientist

• Pursue a PhD in computer science, statistics, mathematics, or a related field
• Gain research experience through internships or research assistant positions
• Attend academic conferences and publish research papers
• Stay up-to-date with the latest developments in machine learning and data science

Head of Data Science

• Pursue a Master's or PhD in data science, computer science, statistics, or a related field
• Gain experience in data analysis and modeling through internships or entry-level positions
• Develop leadership and management skills through volunteer work or extracurricular activities
• Stay up-to-date with the latest developments in data science and business strategy

Conclusion

In conclusion, Research Scientist and Head of Data Science are both important roles in the data-driven world we live in. While they share some similarities, they differ in their responsibilities, required skills, educational backgrounds, and more. By understanding the differences between these roles, you can make an informed decision about which career path is right for you.