Without the right passion, data science is a tough nut to crack. Aspiring data scientists can’t forge a strong career based on the hard skills of programming, mathematics, and statistics alone; soft skills are crucial for realizing their career ambitions.
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The Importance of Soft Skills for Data Scientists
Google conducted a study a few years ago to identify the most productive and innovative teams in an organization. It found that the best groups were not always the top technical talent. Instead, they turned out to be interdisciplinary teams that had professionals who demonstrated good communication, insights about others, and empathetic leadership.
These members enhanced overall collaboration, which in turn improved business outcomes.
Data science is a human pursuit. Organizations bring data scientists to augment their IT infrastructure by adding a humanized, unique angle and specialized skill sets. Therefore, in addition to mastering technical skills, data scientists must polish their soft skills to achieve their career potential.
There is a wide range of soft skills for data scientists that can aid professionals in generating business value for their company and boost their career trajectory. The role of a data scientist is fluid, and each data scientist will have a unique experience and comprehend their work differently because data science environments are distinct and inimitable.
The Data Scientist Skill Set
A firm grasp of the following soft skills for data scientists can serve you throughout your career:
A data scientist should have a knack for linking business orientation with the scientific, analytical, and technical facets. They must communicate their findings to business users and decision-makers and explain what value these insights can bring to the business.
This research must be conveyed effectively to both technical and non-technical audiences. In this way, they can promote data literacy within the organization, which can shine a spotlight on their contribution and make their role more visible across departments.
Intellectual curiosity inspires data scientists to look for answers to address business crises. Professionals can go beyond initial assumptions and surface results. A data scientist must be curious enough to unlock solutions to known problems and uncover hidden, overlooked insights. As a result, they derive a higher quality of knowledge from their data sets.
3. Business Acumen
Data scientists have to deal with a massive amount of knowledge. If they don’t translate it effectively, this priceless information goes down the drain because upper-level management never gets to use it to make business decisions. Data scientists need to appreciate current and upcoming industry trends and acquire basic business concepts and tools.
They also must strive to obtain an extensive understanding of which strengths and weaknesses define their current organization. A shrewd know-how of their organization’s business objectives and market position can enable them to provide answers to everyday business problems and use data to accelerate their organization’s future growth.
Storytelling aids data scientists in conveying their results logically and clearly. It takes data visualization to another dimension, allowing decision-makers to see things from a new perspective.
A compelling storytelling approach builds a strong data narrative where stakeholders attain a new sense of understanding about the data presented and use it to support their decisions going forward.
Adaptability is one of the most sought-after soft skills for data scientists in contemporary talent acquisition. Because technological innovation and implementation are accelerating, professionals have to quickly adapt to the latest technologies. As a data scientist, you have to stay on your toes and respond to shifting business trends.
6. Critical Thinking
Data scientists should be critical thinkers. It allows them to perform an objective analysis for a given problem, empowers them to frame questions correctly, and determines how their findings can help bring an organization closer to a desired course of action.
Analyzing problems objectively during data interpretation is crucial before establishing an opinion. This objectivity encourages data scientists to take a closer look at the data source, examine all problem angles, and remain curious — removing bias from the final output.
7. Product Understanding
Designing models isn’t the entire job. Data scientists have to offer actionable insights that can improve product quality. By gaining a complete product sense, professionals can accelerate quickly with a systematic approach.
They can bootstrap models and enhance feature engineering. Additionally, this skill also aids them in perfecting their storytelling, revealing overlooked thoughts and insights about products.
8. Team Player
Data scientists don’t work inside a bubble, and they must recognize the importance of teamwork and collaborate effectively with others. They need to listen to other team members and use that input to their advantage.
How to Improve Soft Skills for a Data Scientist Career
To improve your soft skills, Glassdoor suggests:Taking an online course. Students can learn anything from hard skills such as Photoshop and network engineering to soft skills like project management and negotiation.
Get feedback from others. Ask others for an assessment of your strengths and weaknesses. Observe and listen to those who have a good rapport with others.
Get a coach. A coach can tailor the learning and practicing process for your personal needs to help you develop specific soft skills quickly and effectively.
Practice with a friend. Practice negotiating skills by asking for a salary raise, a promotion, or a better benefits package. Have your friend play your boss and give you feedback about your proposal.
The Real Benefits of Soft Skills
Everyone can become well-versed in soft skills. A study found out that a factory achieved a nearly 250 percent return on investment when it chose to educate employees with a training program for soft skills. Soft skills can boost productivity, efficiency and support decision-making.
Plus, soft skills will be valued in tomorrow’s automated workforce. The World Economic Forum (WEF) predicts that automation will result in a net increase of 58 million jobs.
About two-thirds of the jobs transformed by automation will become higher-skilled, while the remainder will be lower-skilled.
Automation will take over the more repetitive and dangerous tasks, freeing humans to do more challenging work that incorporates soft skills — interfacing with customers, developing better products, and managing those robots.