Non-Technical Skills for Data Science Professionals
- Learning Ability
- Writing and Reporting
- Public Speaking and Presentation
- Coordination and Leadership
- Business Practices
Data science may represent the juncture of several highly-technical fields, including statistics and computer science, but it also demands a variety of soft skills to augment professional expertise. Data scientists enjoy a widespread surge in demand across many industries, which has fueled expectations of rewarding career options and opportunities. However, students and new professionals can’t just rely on their degree and technical ability to carry them to long-term success. Many employers prefer data scientists who have a solid skill-set that goes well beyond the confines of their field.
Related resource: 30 Best Master’s in Data Science Degree Programs
1. Learning Ability
Data science is an emerging field, so those working in it can expect their roles to continue evolving in the years ahead. Professionals can’t afford to become complacent or stop seeking opportunities to explore new aspects of their work. There is also a significant learning curve in most career paths, so constant self-improvement is an essential asset. After gaining some experience in entry-level programming or database work, new professionals often move towards an analyst or formal data scientist position.
2. Writing and Reporting
Like any other team member in a company or organization, data scientists are generally expected to create written reports that detail the results of their work. Reports may be for sharing updates between team members, tracking progress or preparing a statement for executives. Basic research, writing and editing skills can be invaluable to any technical professional, even if it’s just to improve e-mail etiquette.
3. Public Speaking and Presentation
Data scientists also present their findings or project results verbally, whether it’s to their coworkers or senior decision makers. Data science students should consider adding a few classes oriented around public speaking and presentation to help prepare them for these tasks. Presenters also need to understand the knowledge level of their audience and adapt their message or delivery to ensure they communicate effectively.
4. Coordination and Leadership
Interpersonal communication, teamwork, and leadership are among the most important soft skills for any technical professional. Even though data scientists spend a lot of their time looking at a computer monitor, they are almost always coordinating with others and working as part of a larger team on projects, according to Forbes. They also need to know how to educate or communicate with team members without confusing or overwhelming them.
5. Business Practices
Many employers hire data scientists because they want to harness the power of information and use it to increase the value of their business. Essentially, data scientists need to understand how their activities and results impact the big picture. They need to know enough about basic business practices and their employer’s specific industry to make informed and value-oriented decisions.
There is always room for improvement, so an active professional should seize new opportunities to build and round out their abilities. Improving a few of the essential soft skills can make a huge difference for data scientists who want to explore their field and get the most out of their career.