These Masters build on a series of courses already in place which have marked out HEC Paris as a leader in teaching the interdisciplinary world of data science. This so-called “fourth paradigm” in the scientific world is an expansion of the data analysis fields of statistics, predictive analytics and data mining. The likes of Peter Ebbes and Gilles Stoltz have been teaching these topics at HEC Paris for years. The two research professors and members of the GREGHEC Research Group continue to spearhead efforts to provide insight into data culled from both structured and unstructured fields.
Bringing Statistics Alive
“In teaching data science and statistics you should tailor your courses to suit both your personality and those of your students,” exclaims Gilles Stoltz, reclining in his new office in V building. “Because it’s important to galvanize them and convey your enthusiasm. Let’s face it, when they set the cursor, it brings alive a subject-matter that on paper doesn’t seem very inspiring at first.” The co-author of Statistique en Action draws on exactly a decade of teaching at HEC Paris to explain his pedagogic approach. And, even if his colleague Peter Ebbes has been on the HEC Paris campus half those years, they both share similar beliefs on transmitting data science: “My classes are never one-way monologues,” explains Ebbes. “I quiz the students, we explore case studies together, the classes become conversations which keep them engaged. Okay, it’s sometimes tricky when I have 70 in the core classes, but I remain very keen on a participatory approach and we have some lively exchanges.”
Gilles Stoltz has been teaching his L3 statistics class since 2007 in a course with the logo “for today’s citizens and tomorrow’s leaders”. In the space of 20 hours he and his team of five-fellow statisticians present the fundamental theories to five classes of international students and eleven classes of French students. “I love this kind of teaching at HEC. It’s like doing theater! In theory they’re not too enthusiastic about statistics but by basing my teaching on a multitude of examples, I manage to gain their enthusiasm.” Stoltz shares with us one of the most popular practical cases amongst students. “Surprisingly, one focuses on the Iranian presidential elections of 2009,” he explains, “that’s when the Americans thought they had found a smoking gun proving the showdown between the incumbent leader Mahmoud Ahmadinejad and opposition candidate Mir Hussein Mousavi had been rigged. The Washington Post published an article, “The Devil Is in the Digits”, which analyzed the results using uniform distribution for the last digits of the vote but with an incorrect methodology. “They should have used the Chi-square test of goodness of fit! They would have seen that the P value is 7%, which is a typical value. So, as several statisticians pointed out at the time, the data is in no way a blatant proof of manipulation. The students like this example, it brings to life a situation which has an impact on the geopolitical world.”
A Multi-disciplinary Field Invites a Multiplicity of Students
Peter Ebbes focuses his teaching on business analytics, marketing research and marketing models. For the former professor at the prestigious Penn State University, there are three skills the students should aim at acquiring: “Advanced knowledge of statistics and math, IT and a substantive field like marketing”.“Many graduates master two of these three skills, very few manage to acquire all three,” he explains from his office in W1 building. “Added to this, it’s a real plus nowadays to acquire all-round knowledge on computer storage, moving data from one place to another. Acquiring all these is the big challenge we now face as we are challenged by this quantum increase in data.” The multidisciplinary nature of data science is reflected in the diversity of participants in Ebbes’ courses. “The catchment is really wide,” he points out, “We have some interesting characters in the MBA courses, there’s one from Google analytics, another with a PhD in philosophy, for example. The latter has provided some brilliant and unexpected insights into the case studies we’ve been working. This diversity really enriches our work.”
Important Backing From HEC Foundation
Could this variagated horizon be why there is an increased call for such data science and analytics experts like Peter Ebbes? In the United States alone, it is believed the gap in data scientists could be at 190,000. “There is a clear demand,” explains Ebbes, winner of the 2016 HEC Foundation best researcher award. “Businesses are hungry for specialists who can sift through their data. And, meanwhile, our research benefits from access to their raw data. It’s a win-win situation.”
The decision by HEC to purchase an eye-tracker has also helped researchers at the school better study consumers’ purchases online. “For example, what do people do with online reviews? Do they read them? How many? How does it influence their decisions?” asks Peter Ebbes. “With a PhD student, we’ve been overlaying the data with the eye-tracker which helps us know how and what to read.” Ebbes insists the help the HEC Foundation has given in funding such programs has been vital “It’s one of the most supportive in Europe, on a par to the support that institutions receive in the US,” he insists. The Dutch academic also stresses the positive impact HEC’s business connections has on research. “The school has a long history of collaboration with top multinational companies, it’s very important to work with them. I only wish French businesses were more aware of the opportunities there are to collaborate with us on research.”
Paris-Saclay University on the Data Horizon
The proximity of major companies are a clear asset in HEC’s teaching of data science, according to Gilles Stoltz. The teacher of Sequential learning and sequential optimization at M2 level believes the best way to transform the courses’ theories and field work into practical applications is through internships. ““Some of my PhD students in math have been hired by private companies under the CIFRE agreement,” explains Stoltz. “They have access to field data and have to develop theories based on their academic trainings and on-the-field experience. When they elaborate an idea for an algorithm they needs to code it, sometimes using all the big data framework and environment. The private sector provides the ideal setting for this. Not to mention the fact that their salaries are heavily subsidized for the companies!”
With this in mind, Gilles Stoltz believes the rapprochement between HEC Paris and the other establishments in Paris-Saclay University can only be positive. But he is also enthusiastic about the developments developments at HEC Paris. “HEC wants to recruit a senior academic in business analytics, and we’re in a good state of mind. Statistical tools are being used in a multiplicity of classes, especially involving marketing and finance.” In the early 2010s, French affiliate professors of marketing had only a qualitative approach, Stoltz maintains. “Nowadays, we also have new younger academics like Daniel Halbheer, Cathy Yang and Ludovic & Valeria Stourm who are teaching marketing in a very quantitative way. Offering the two approaches is a real progress.” And the dynamic researcher concludes the department’s approach has made teaching data science a less dense and impersonal challenge than mirror courses on the other side of the Atlantic.
