What Is a Data Science Unicorn?

The Data Science Unicorn

A “data science unicorn” is akin to Micheal Jordan. But instead of the sport of basketball, it’s the game of data science. It’s a term used to describe an individual who has a rare combination of technical and non-technical skills in the field of data science.

As such, a data science unicorn is invaluable to organizations looking to leverage the power of data science to gain a competitive edge. In this article, we will take a look at some of the technical skills and soft skills a data science unicorn will possess.

Table Comparison: Data Science Unicorn vs Data Scientist

Before we begin, I just want to outline some of the key differences between your average data scientist and a data science unicorn.

Aspect	Data Science Unicorn	Data Scientist
Expertise	Possesses a wide range of skills and expertise across multiple domains within data science.	Specializes in one or more specific areas of data science.
Skill Set	Proficient in various areas like programming, statistics, machine learning, domain knowledge, big data technologies, communication, and more. They got it all.	Focused on a specific skill set, such as statistical analysis, machine learning, data cleaning, etc.
Roles	Can perform a variety of roles within data science, including data engineering, machine learning, data analysis, domain expertise, and more.	Primarily involved in one or two data science roles, depending on specialization.
Scope of Work	Can take on end-to-end projects, from data collection to model deployment and business impact assessment.	Often focuses on specific phases of a project, such as data analysis, modeling, or interpretation.
Breadth vs Depth	Balances breadth and depth of knowledge across various areas.	Focuses on in-depth knowledge within their specialized field.
Versatility	Highly versatile, can adapt to different projects and roles within data science.	Specialized and less adaptable to roles outside their specific expertise.
Industry Impact	Can make significant contributions across various data science domains and solve complex cross-functional problems.	Makes significant contributions within their area of specialization.
Learning Curve	Requires continuous learning to maintain expertise across diverse domains.	Requires continuous learning to stay updated in their specialized area.
Job Market	Rare and in high demand due to the unique combination of skills.	High demand, with a focus on specific roles and skills.
Collaboration	Can collaborate effectively with experts from different domains within data science.	Collaborates well within their specialized team or with domain experts.
Job Titles	May have titles like “Lead Data Scientist,” “Principal Data Scientist,” “Data Science Manager,” etc.	Common job titles include “Data Scientist,” “Senior Data Scientist,” “Machine Learning Engineer,” etc.
Examples	Possesses skills in programming, statistics, machine learning, domain knowledge, big data technologies, and more.	Specializes in machine learning model development, statistical analysis, data preprocessing, etc.

Technical Skills

A data science unicorn is highly sought after due to its rare combination of technical data science skills and can often command a high salary. From programming to machine learning, here are some of the skills a data science unicorn has proficiency.

Programming – Be able to write code in languages such as Python and R.
Machine learning – Possesses a wide range of skills in order to effectively use machine learning for their projects.
Math and statistics – Knowledge to identify patterns and anomalies in large datasets.
Subject matter expertise – Be proficient in the related project topic.
Traditional research – Possesses many of the same traditional research skills that academics typically possess.
Database technologies – Use database techniques effectively such as SQL and NoSQL

Soft Skills

A data science unicorn has the unique ability to understand the needs of the business. Then, they can translate those into the right data science questions and apply the right techniques to answer those questions accurately and efficiently.

Here are some of the soft skills of a data science unicorn:

Communication – Able to break down complex concepts into easily digestible language.
Team building – Engage and energize various team members to complete projects successfully.
Project management – Sought out to lead large teams and projects and perform project management roles.
Problem-solving – Ability to understand the big picture and to bring order to chaos.
Results-oriented – Create innovative solutions from solid technical expertise to complex problems.

Conclusion: The Data Science Unicorn

A “data science unicorn” is a term used to refer to an individual who possesses the rare combination of technical skills and business acumen necessary for success in the field of data science.

These data scientists are rare individuals who are the “total package” in the world of data science. Finally, they are often highly compensated for their skills and are in high demand due to their rare set of capabilities.