"Analytics isn't something you learn by watching. It's something you learn by doing."
Hands-on projects
I joined Nazareth in 2024 as one of the founding faculty members for our new Master of Science program in business analytics and AI. Before academia, I spent several years in data driven business and strategy consulting helping companies figure out where to invest their marketing dollars and which strategies would actually move the needle.
My philosophy has always been simple: Analytics isn't something you learn by watching, it's something you learn by doing. I load my courses with hands-on assignments, real case studies, and projects that mirror actual workplace challenges. When something feels hard at first, we work through it together until it becomes second nature. That's how confidence gets built.
My vision for students
I want students to walk out of my classes ready for day one on the job. Not just understanding concepts, but knowing how to apply them under pressure. Every assignment, every case study, every class discussion is designed to close the gap between the classroom and the real world. When my students interview for jobs, they don't just talk about what they learned; they show work they've actually built.
Forward-looking classrooms
The field of analytics changes fast. Technology evolves, new tools emerge, and what's cutting-edge today might be standard tomorrow. I encourage students to bring in articles they've read, share trends they've noticed, and challenge the ideas we discuss in class. The best sessions are the ones where a student teaches me something I didn't know.
What I love about teaching
Data Analysis and Decision Making and Spreadsheet Applications are where I get to work with undergraduates who are often touching analytics for the first time. There's nothing like watching a student who walked in thinking "I'm not a numbers person" realize they absolutely are. In Data Analysis and Decision Making, students complete a simulated internship (Simternship) where they become data analysts at a fictional company. They live the life of an analyst and see what the day to day emails and tasks look like. By the end, the work feels natural because they've done it, not just read about it.
Why Naz?
Small class sizes mean I actually know my students. I know who's balancing a full-time job with grad school, who's pivoting careers after a decade in another field, and who needs a little extra encouragement to see what they're capable of. Naz students ask questions. They challenge ideas. They want to understand the "why" behind everything, not just the "how." That curiosity makes this place special.
What makes my graduate classes different
My graduate sessions are conversations, not lectures. Students bring their professional experiences into the room, challenge ideas, and learn from each other as much as from me. I ask a lot of questions and I'm comfortable with silence. The best insights come when students sit with a problem long enough to find their own path through it. We debate real cases from companies like Chevron and Google, and I expect students to push back when they disagree. That's where the real learning happens.
Supporting changemakers
Analytics is powerful, and power comes with responsibility. In my classes, students learn to root out bias from AI systems before those systems make decisions about real people's lives. We examine how algorithms can quietly disadvantage minority communities, and how to fix that.
But changemaking isn't just about critique. It's about action. I want my students to use their skills to uplift the communities around them. That means helping small businesses make sense of their data, enabling local organizations to operate smarter, and giving minority-owned businesses the same analytical edge that big corporations take for granted. Data shouldn't just serve the companies that can afford expensive consultants. My students learn to democratize that power.
When a graduate of my program walks into a local business and helps them understand their customers, streamline their operations, or make a case for funding, that's Change. Real Change. Right here in our community.
Advice for students
Get comfortable being wrong. Your first analysis will have gaps, your assumptions will break, and the data will surprise you. Success in this field doesn't come from being naturally gifted at math, it comes from the ability to look at what didn't work and ask "What did I miss?" and "Why?" without losing momentum. You are an explorer and a detective. And what is a detective without questions?
Courses I teach
- Data Analysis and Decision Making
- Spreadsheet Applications
- Quantitative Analysis
- Talent Analytics
- Integrative Business Analytics
- AI Innovations in People Analytics
Fast Facts
- Industry Background: Data-driven strategy consulting for Fortune 500 clients at ZS Associates and IBM
- International Speaker: Presented "Democratizing AI Analytics Across Every Business Function" at AI Symposium 2025 in Czech Republic
Student Perspective
“While championing a down-to-earth attitude, Professor Shukla still challenges those he teaches. No question is dumb, no concept is beneath his explanation. He can turn individuals unfamiliar with his field — but seeking to learn — into strong, equipped talent with more than enough knowledge to enter the workforce. Professor Shukla embraces his humanity in the classroom; his use of memes and jokes keeps the atmosphere fresh, inviting, and authentic. He doesn’t just teach, he mentors and builds with his students so past their time at Naz, they’ll be able to overcome new obstacles.”
— Anthony S. Bray III, grad student in Nazareth’s business analytics and artificial intelligence master’s program
Expert source
What can go wrong when a store captures customers’ biometric data and uses facial recognition technology to assess customers? WROC-TV Channel 8 turned to Rajat Shukla for insights.
