4 Essential Skills Often Underestimated by Data Scientists

Hi! 👋 I am Roxanne, an Ex-IBM Data Scientist and a Coursera Instructor of Machine Learning. Subscribe to my newsletter “Is Data Science Still Sexy” and join the 1000+ readers today!

Seeing the astonishing capabilities of the latest version of ChatGPT makes me wonder, what are the essential skills of a Data Scientist that even AI can’t easily replace?

I found a very good article written by Sara A. Metwalli, published on Towards Data Science in 2020. The 4 skills she mentioned are what I would urge my fellow Data Scientists to have immediately, especially in the era of GenAI (I would say she has very good foresight to have talked about them 3 years ago 😁 ).

1. Clear and Effective Communication Skills 🦜 

A Data Scientist's work involves extracting valuable insights from complex data sets. Yet, presenting these findings in a clear and compelling manner is an art in itself (here I found a good course on Communicating Data Science Results). Clear and effective communication skills are the bridge that connects data-driven discoveries to actionable decisions. Data Scientists who excel at this skill can transform abstract numbers into compelling narratives, making their insights accessible and influential.

Whether you're explaining a sophisticated model to non-technical stakeholders or collaborating with cross-functional teams, your ability to convey complex ideas with simplicity is invaluable. In a world where AI can’t explain itself well, your communication skills become your superpower.

2. Basic Business Understanding 🧠 

To be indispensable in Data Science, it's essential to go beyond data manipulation and prediction. Understanding the fundamental business context is like having a compass in the data wilderness. You'll know which data points are truly relevant, which models align with business objectives (think about predictability VS interpretability 💬 ), and how your work impacts the bottom line.

AI tools can provide data-driven insights, but it's up to the Data Scientist to interpret and integrate these insights into a broader business strategy. A solid grasp of business fundamentals sets you apart, ensuring that your work isn't merely data analysis but a catalyst for business success.

3. Collaboration and Teamwork 😎 

As a Data Scientist, you never work alone ⚒️ . You’re always part of a team working towards the same goal. You interact with managers, designers, marketers, and all kinds of stakeholders of your project. Collaboration and teamwork skills are the glue that binds these teams and keeps the project on track.

AI 🤖 tools may offer solutions, but they can't replace the synergy of a well-functioning team. The ability to collaborate, understand different viewpoints, and work cohesively toward a common goal is a hallmark of a highly effective Data Scientist. It's a skill that's hard for AI to replicate.

4. The Ability to Maintain the Code 🤪 

Automated tools can write code, but maintaining and optimizing it requires a human touch. An essential skill for Data Scientists is the ability to ensure that the code and models remain robust, efficient, and up-to-date. This includes addressing mission-critical issues, updating libraries, and keeping the codebase organized and scalable.

By excelling in code maintenance, Data Scientists add enduring value to projects. AI tools can generate code, but they lack the expertise to ensure long-term reliability and performance 👻 .

While AI and automated tools are formidable, Data Scientists can secure their roles by focusing on these essential skills. Clear communication, business acumen, teamwork, and code maintenance are the human elements that AI can't replace. By honing these competencies, we will remain the driving force behind data-driven innovation and decision-making in the AI-powered world 🚀 

That’s a wrap for today! Thanks for reading and subscribing 🫡 . I’ll see you in my next one 👋 .