Listen here:
Gene Ray is an Atlanta-based data science and statistical expert with over 20 years of experience in education and healthcare.
He is currently a Professor of Data Science and Biostatistics and the Director of the Data Science and Analytics Ph.D. program. Before this, he was a Director of Program Management and a Senior Director of Biostatistics and Programming for ConcertAI. He was the founding Director of Kennesaw State University’s Center for Statistics and Analytical Research (CSAR), which is now the Center for Data Science and Analytics (CDSA). Dr. Ray has worked with Real-World Data (RWD) and associated problems since 2000, when he started as a Statistician for CIGNA and moved into a research position at Thomson Reuters before transitioning into academics at KSU in 2011.
He completed an undergraduate and masters degree at Middle Tennessee State University. He earned his Ph.D. in Biostatistics from the University of Louisville’s School of Public Health.
Connect with him to learn more.
Listen to the Podcast Here, or Find it Wherever You Get Your Podcasts:
Here are Five Things We Cover:
1. The #1 Skill You Need to Succeed in Data Science:
Math is important, but the real game-changer? Programming. If you want to work in data science, Python should be your first language. It’s widely used across industries and is essential for data manipulation, visualization, and machine learning.
2. Do You Really Need a Master’s or PhD?:
Not always! A bachelor’s degree is often enough to land an entry-level data science or analytics role. However, if you want to work on advanced AI, machine learning, or research, a graduate degree may be worth pursuing.
3. The Best Way to Get Hands-On Experience:
Employers love real-world projects over just coursework. Get ahead by:
✔️ Working on research projects with professors
✔️ Joining Kaggle competitions
✔️ Creating side projects using real datasets
✔️ Showcasing your work at conferences or online
One student even landed a job on the spot by presenting their analytics project at a research fair!
4. AI Won’t Replace Data Scientists—But It Will Change the Job
AI tools like ChatGPT automate tasks, not jobs. Companies still need data scientists to interpret results and make business decisions. Learn how to use AI to enhance your work rather than fear it.
5. Soft Skills Matter More Than You Think
It’s not just about coding. Presentation, communication, and problem-solving skills will set you apart. Companies want data scientists who can translate complex insights into actionable business strategies.
Here are Three Actionable Takeaways From This Episode
- Start Building Your Data Science Portfolio Now: Don’t wait until graduation to gain experience. Work on real-world projects by participating in Kaggle competitions, research studies, or personal data analysis projects. Showcase your work on GitHub or LinkedIn to stand out to employers.
- Master Python and Learn How to Work with Data: Programming is the foundation of data science. Focus on Python for data manipulation, visualization, and machine learning. Start with small projects, then move on to more complex datasets to build your skills.
- Develop Soft Skills to Communicate Insights Effectively: Technical skills alone won’t get you hired. Learn how to explain data findings to non-technical teams, present insights clearly, and collaborate across departments. The best data scientists know how to translate data into business impact.