The MS Analytics Program at Texas A&M University recently celebrated its fourth cohort of graduates — a group that included the program’s 100th all-time graduate and most recent recipients of the coveted Roland H. Acra ’86 Master of Science in Analytics Award.
A total of 40 students gathered May 9 at Houston’s CityCentre to present their capstone projects to friends, family and employers. A graduation celebration followed.
“I can’t believe it’s been five semesters,” said one graduate. “I remember the day I showed up in this building and didn’t know anybody. Now, we all leave as one big family — an Aggie family.”
To date, 103 students have earned master’s of science in analytics degrees through the program, launched in fall 2013 by the Texas A&M Department of Statistics in partnership with Mays Business School and bolstered by a significant donation from business analytics software and services leader SAS. Students participate in a rigorous curriculum that consists of 75 percent statistics and 25 percent business, in addition to a work-based capstone project.
“That is the cornerstone of our program,” said Dr. Simon Sheather, Professor and Program Academic Director as well as Interim Director of the Texas A&M Institute of Data Science. “We encourage students to grow within their organizations and pioneer analytics.”
Upon acceptance into the program, each student is assigned a faculty member or a subject matter expert who serves as their project coach. Throughout five semesters, the students and coaches meet in an effort to produce a predictive model. Their projects span many different industries, including oil and gas, healthcare, retail, hospitality, ecommerce and marketing.
As part of this month’s graduation festivities, two students — Diego Molinari and Marek Danis — were presented with the coveted Roland H. Acra ’86 Master of Science in Analytics Award recognizing the most outstanding master’s project in analytics completed during the previous academic year. With so many outstanding projects, it’s a selection process that gets harder for the committee every year, Sheather said.
Molinari’s project, “Describing and characterizing well recovery across major basins in U.S. Onshore,” used public data to model well hydrocarbon recovery in the major unconventional liquid-rich basins (shale oil) in U.S. Onshore as a function of spatial, geological and completion variables.
“The program was a phenomenal experience for me,” Molinari said. “It taught me concepts that allowed me to see the world in a new way; I learned methods and tools which allowed me to build and interpret descriptive and predictive models with a wide array of business applications.”
Danis’ project, “Saving Lives With Statistics,” focused on the safety of their employees at an oil and gas servicing company. He analyzed the impact of their various safety initiatives and determined how effective each one is in reducing accidents — invaluable information that previously was not available.
“I was missing the scientific factor,” Danis said. “That is why I decided to join the MS Analytics Program at Texas A&M University and found this to be the right step. My capstone project was about workplace safety, which doesn’t sound very scientific, but Dr. Sheather showed us how to tackle any business problem, technical or not, in a scientific, data-driven way with empirically proven results.”
“Both projects are incredible,” Sheather said. “It speaks volumes; the program is designed to teach students to apply these methods to solve problems using data and to ultimately predict the future.”
Molinari is a petroleum engineer with eight years of international oil and gas industry experience. In his current role, he is part of Anadarko’s Advanced Analytics and Emerging Technologies (AAET) team, helping the company adopt data analytics and develop digital technologies to operate more efficiently.
Danis, after finishing his undergraduate degrees at Getttysburg College and Columbia University in STEM fields, joined Schlumberger as a leading technology company. He was running field operations in the drilling domain.
For more information about the MS Analytics program, visit http://analytics.stat.tamu.edu/.
To learn more about the Texas A&M Department of Statistics, visit http://www.stat.tamu.edu/.
Contact: Myra Gonzalez, (979) 845-6855 or email@example.com