Darden | Mr. Strategy Manager
GRE 321, GPA 3.5
Ross | Mr. Airline Engineer
GMAT 730, GPA 3.73
Harvard | Mr. Sovereign Wealth Fund
GMAT 730, GPA 3.55
Stanford GSB | Mr. Corporate VC Hustler
GMAT 780, GPA 3.17
Emory Goizueta | Mr. Multimedia
GRE 308, GPA 3.4
Harvard | Mr. Smart Operations
GMAT 760, GPA 4.0
Wharton | Mr. Marketing Director
GMAT 710, GPA 3.3
Ross | Ms. Healthcare Startup
GRE 321, GPA 3.51
Kellogg | Mr. Real Estate Finance
GMAT 710, GPA 3.0
Harvard | Mr. Healthcare Fanatic
GMAT 770, GPA 3.46
Georgetown McDonough | Ms. Air Force
GMAT 610, GPA 3.8
Stanford GSB | Mr. JD To MBA
GRE 326, GPA 3.01
Harvard | Mr. MacGruber
GRE 313, GPA 3.7
Berkeley Haas | Mr. Poet At Heart
GMAT 740, GPA 3.7
Yale | Mr. Ukrainian Biz Man
GRE 310, GPA 4.75 out of 5
Darden | Mr. Former Scientist
GMAT 680, GPA 3.65
Stanford GSB | Mr. Sustainable Business
GRE 331, GPA 3.86
Wharton | Mr. Microsoft Consultant
GMAT N/A, GPA 2.31
Yale | Ms. Impact Investing
GRE 323, GPA 3.8
Cornell Johnson | Ms. Food Waste Warrior
GMAT Not written yet (around 680), GPA 3.27
Stanford GSB | Ms. Future Tech Exec
GMAT 750, GPA 3.4
Kellogg | Mr. Finance To Education
GMAT 730, GPA 3.4
Rice Jones | Mr. Back To School
GRE 315, GPA 3.0
Columbia | Mr. Aussie Military Man
GMAT 710, GPA 3.0 (rough conversion from Weighted Average Mark)
Harvard | Mr. Hopeful Philanthropist
GMAT 710, GPA 3.74
Stanford GSB | Mr. FinTech
GMAT Not Taken Yet, GPA 3.5
UCLA Anderson | Mr. Analytics Man
GMAT 740, GPA 3.1

B-School Master’s: Spotlight on NYU Stern

NYU Stern MS in Business Analytics graduate Tim Long

NYU Stern MS in Business Analytics graduate Tim Long

Tim Long had a background in data, but not in big data. He’d spent nearly nine years at Micron Technology in Boise, Idaho, most of that time in IT. “Moving data around and writing software was definitely part of my past,” Long says. But after he moved into a new position, as a process and measures program manager for the company’s global HR department, he saw both the potential to use data analytics in the job, and his own weakness in that area. The department was ripe for a range of data-related processes – causal modeling, predictive data, visual storytelling of what data showed.

What I quickly learned was that there was this huge opportunity to apply more advanced analytics,” says Long, a 36-year-old Wyoming native with a BS in mechanical engineering from the University of Wyoming. “I realized I really didn’t have the skills that I wanted to have in order to be able to lead the organization forward.”

To bring himself up to speed, Long headed east in 2013, to NYU Stern School of Business, for their brand-new master of science program in business analytics. “There’s what you learn and there’s what you take away from the program,” Long says. “What I learned is a lot of powerful techniques in working with data and how to present it in a way that is meaningful for the business. What I took away from the program was not just that but really this new awareness of all of these topics to learn more about. It introduced me to this whole new world of what’s possible with data.”


Coming back to Micron, he shared his new knowledge and skills with his team, dramatically boosting their impact – even outside their department, he says. “One of the things I’m most proud of in my organization is that my team is known as a very talented analytics function at the company, and not just for HR data,” Long says. “We’ve had the privilege to participate in supporting analyses from other functions, for example working with our sales teams, working with our supply chain teams, and we’re really looked to as a leader in this space. We’re able to then go out and serve the company, not just in the HR space but in broader business problems.”

The cohort-based Stern program also added significantly to Long’s professional network. “Something that I value very highly is just this connection that I have with these amazing people that I went through this program with. It’s a globally diverse program with people from all over the world participating, and it has this component of classroom learning where everybody gets together for a week at a time to learn from the professors and each other,” he says. “I’ve left this program with this very rich and highly valuable network of peers that would’ve otherwise been very difficult to establish, especially for someone in Boise, Idaho.”