M2 Choice – Economic Theory and Econometrics (ETE)

M2ETE_CurrentStudentCurrent student – Till Kov

Which aspects of your chosen program were the most challenging?

ETE is a very theoretical and mathematical program. For me, the most challenging aspect was the level of mathematics which is required for some courses. But this is also due to the fact that I have a less strong background in mathematics than many other ETE-students because I did my undergrad studies in Sociology, Politics and Economics.

Which was your favourite course(s) and why?

In the first semester, my favourite course was Game Theory. The teaching style and the structure of the course were both really good. However, it had quite some overlap with content that we covered in the M1. In the second semester, my favourite course so far is the optional course in Environmental economics. The course mainly consists in reading and critically discussing current papers from the field, which helps me in developing own research ideas for the M2 thesis and for the PhD.

What do you plan to do next?

Over the summer, all ETE students will write their M2 thesis. After that, I will take some time to relax before I will start doing a PhD with a focus on environmental economics.

Alumni – Oscar JaraM2ETE_Alumni

What are you up to now?

I am currently following the DEEQA program, which is the first year of the PhD at the Toulouse School of Economics. In DEEQA,  you must choose seven courses that are related to your field interests and write a paper at the end of it. During this year we can also attend seminars and workshops, where scholars from the most prestigious Universities of the world come to TSE to present their latest and most significant work. I have been in many of these and not only it is academically enriching, but also gives you a sense of the academic community that we are intended to join in the (near) future.

What skills acquired from TSE do you find useful in your work?

In DEEQA we have two main duties: attend and participate actively in lectures and write a paper at the end of it. For the lectures, since most of the workload is focused on discussing and giving critical opinions about papers, it is necessary to have a solid background in economics. In the core and elective courses of the M2 ETE, we were required to learn the main economic principles – which demanded many hours of dedication and effort. For the DEEQA paper, the M2 ETE is of great help because at the end of it we had to submit and defend a paper. After one year learning the different economic theories, one is supposed to come up with a research question and work on it. This is the first time when we are supposed to actually create a model regarding a question that we think is both interesting and relevant. The exercise of thinking the best way to express ideas into equations is really challenging and compels you to go deeper in the related literature. In DEEQA, we can continue working on the ETE’s thesis or find another more interesting – and relevant –  research question.

M2 Choice – Econometrics and Empirical Economics (EEE)

Current student – M2EEE_CurrentstudentGaudéric Thiétart

Which aspects of your chosen program were the most challenging?

I would say what is the most challenging in M2 EEE is using and learning several software languages at the same time.  Some teachers prefer Stata or R, others want you to learn Matlab or Eviews. Sometimes it can be quite confusing, but it is also very useful, as we will know how to adapt depending on the software used by our future company.

In addition, and in a more personal way, it was quite challenging for me to go back to TSE after my gap year. Even though I studied one semester abroad, the courses I chose were not particularly related to econometrics, which is why I was quite worried about coming back in M2 EEE. I would advise people returning from their gap year to read quickly their M1 courses before beginning their M2. However, do not worry too much, you will not be the only one in this case!

Which was your favourite course(s) and why?

To be honest, I was a bit disappointed with the classes I had during the first semester. I thought that being in M2 would have meant more practical work; however, in my opinion, the courses remained very theoretical. In this sense, I really enjoyed the “Programming in Python” class because our teacher was a Data Scientist from Deloitte in New York City. To have a professor coming from one of the main international consulting firms was interesting to see how the theoretical and programming skills we have are practically used at work. I hope these links between firms and TSE will be improved in the future in M2 EEE.

What do you plan to do next?

In the short run, I will do a six-month internship at la Banque de France. I will work for the Diagnostic conjoncturel (Short-Term Diagnosis) service to help in the forecasting of French GDP and to improve their econometric models. After that my plans are not really defined yet. If I enjoy my experience at la Banque de France, I might keep on working in this macroeconomics/forecasting area. I would also be interested in working for the public sector or in an international agency such as the OECD.

 

Alumni – Joël Brehin

What are you up to now?

During the BND, I found an internship as a data scientist for BI Consulting, consisting in  trying to fit a predictive model of car accidents. After this, I was hired as a general data consultant, potentially called on tasks of data science but also of data engineering. Currently, I am carrying out a mission as a data engineer. This position is a good opportunity for me to develop my skills both in data science and on more technology-related tasks. I was able to learn new programming languages such as Scala and to get a better understanding of distributed architecture for Big Data.

What skills acquired in M2 are relevant for your current position?

During the EEE M2, I was able to get a good theoretical foundation in statistics and econometrics that helped greatly when developing a data science algorithm. Indeed, in contrast to a computer science degree, it gives me a better grasp of the mathematics at work in these models. My studies were also my first experience of programming in Python and R, which are languages I am often using. It was also a good entry point to learn other languages. Most importantly, this experience in programming is something I found a strong liking to, although I had never considered it before. Finally, because  EEE is mostly based on practical applications and group projects rather than finals, my transition to the labour market was easier. I did not take too much time to adjust to hard deadlines, group work and working on my own.

 

 

M2 Choice – Statistics and Econometrics

M2EcoStat_currentstudent2Current Student – Joseph Agossa

Which aspects of your chosen program were the most challenging ?

Among the courses I have chosen this year, I can say that the most challenging for me were Mathematics of deep learning algorithms. Deep learning knowledge can be described in terms of four distinct aspects:

  • Knowledge of multiple models and multiple viewpoints of the domain.
  • Knowledge about the relations between different models and viewpoints.
  • Knowledge of reasoning procedures to solve quantitative and qualitative problems.
  • Knowledge of first principles and knowledge to reason on their basis in order to solve novel or unfamiliar problems

Deep learning algorithms can be successfully applied to big data for knowledge discovery, knowledge application, and knowledge-based prediction. In other words, deep learning can be a powerful engine for producing actionable results.

Which was your favourite course(s) and why? 

My favourite courses were Survey Sampling and Time series because they are very useful and applicable to real life cases. My favorite part of being in a master in Statistics and Econometrics  was being challenged by professors with interesting problems, especially the real application of Time Series, and survey sampling projects.

What do you plan to do next ?

I will start my internship on April 06, 2020 in the international company IQVIA-France in Paris.

I will work as an Economic Statistician in the Real-World Solutions (RWS) Department of IQVIA France, which brings together a team of 100 multidisciplinary and highly qualified consultants in market access, real-life studies, health economics and epidemiology.  Future plan after graduation will be to find a job as a Data Scientist in Paris or Washington.

Internship report: Arthur Biamouret, RATP

Internship report Arthur BWhere did you do your internship and what was your role?

I did a six months internship at the Réseau Autonome des Transports Parisiens – RATP – headquarter in Paris to validate my M1. My mission was to try to design an econometric model to estimate the buses demand in Ile-de-France. I did everything, from cleaning the database to building the econometric model, testing hypothesis, and write a report about my findings. I was part of a team of engineers, and was thus the only person with an economic background. Hence, I was quite autonomous.

How did your studies/courses help you during your internship?

R courses helped me a lot, as it was the software I was working on during my internship, along with Excel and QGIS, a cartography software. Courses in econometrics were of course also very useful. However, I hardly knew how to clean databases, and this is something I regret not having learnt more deeply at TSE. School projects like the Applied Econometrics project taught me how to efficiently communicate and attribute tasks in a group, and it helped me a lot during my internship. My team gave me responsibilities, trusted me, and was always here to help me if needed; this is something I really appreciated. On the other hand, my internship changed my way of reading and learning my lessons. I try now to distinguish between theoretical parts – like mathematical proofs – and practical parts, and focus more on the latter, as they are the most important parts to remember at the end of the day.

How did you find your internship ? What advice would you give to students who would like to find a similar internship ?

I found this internship through the Alumni website. I was then contacted by the team I ended up working with for a call interview. I have to say I found my internship pretty late, and would like to give some advice to students – especially to M1 students – who are searching for an internship. I sent a lot of applications from October, but realised later that I did not adopt the most optimal strategy. I appreciated the Professional Development course, but I think it only gives you bases that you really have to develop to have an original and personal application. It was my first internship, and at first I did not focus enough on concrete skills I had, that are school projects, technical courses like the Empirical Industrial Organization course, software and personal projects. I started by applying for the positions I wanted the most, and I regret having done so. If it is your first internship, I advise you to apply first to positions that are not in your top list to get some practice. I admit I was disappointed by the Business Networking Day in the sense that I was pretty sure to get my internship there, but I later realised this is an event that is mostly useful to M2 students, or to students that already have some experience. However, I still recommend you to go and practise your elevator speech, as it will give you some training for real interviews. Finally, I would recommend sending quite a lot of applications, as the response rate might not be high for your first internship. However, sending them in January instead of October – while still keeping an eye open for potential offers during the autumn period – might be better. Finding your first internship might be hard, but once you get it, it becomes way easier to find other internships. I then worked at Veltys consulting in Paris during my gap year, and found this position quite easily.

TSE Alumni Article – Maguelonne Jarczak, Data Analyst at Airbus

TSE Alumni Maguelonne J

 

What is your position today?

I am working as a Data Analyst at Airbus. I joined in October the Airframe data Analytics (ADA) Team that is in charge of supporting the deployment of data analytics solution for Airframe engineering. Airframe is the mechanical structure of an aircraft.

I am part of a self-organised transnational team of six people. Our mission is to build the transverse referential of data analytics methods and data model for the Airframe community. ADA team delivers transverse activities and projects in these four fields: data exposure, data semantics, data services and data analytics products.

I have for instance projects on composite materials. Structural materials used on Airframe are tested to ensure the right level of performance and the compliance of the raw material with regards to the product specification of the material. I use a data analytics approach to identify any possibility to reduce the level of testing keeping the same level of material quality. I also have a big project to predict gaps and overlapping when we assemble nacelle on an engine.

We are the reference team in data analytics for engineering airframe. It implies a high involvement in the analytics network: animation of the network, sharing best practices, participation to market place, and communication event.

As part of a self-organised team, we are responsible for the organisation team. I have recently been involved in a recruitment process. It was funny to be on the other side!

I recently had the opportunity to become a focal point for eSelf, a community aiming to develop empowerment in Engineering Airframe. The term empowerment refers to measures designed to increase the degree of autonomy and self-determination in people and in team in order to enable them to represent their interests in a responsible and self-determined way, acting on their own authority. My work has great variety!

 

What was your path from you Master’s graduation to this current post?

I was enrolled in Master 2 Econometrics and Statistics and in apprenticeship as a data analyst at Airbus in Quality Procurement. I was looking for a position of data analyst, with a preference for the aeronautic sector. I found this opportunity through the Alumni website and I applied for it. I passed two interviews with HR and two with the team. I was also involved in a recruitment process with Air France for a position in Marketing.

Today I am very happy to be part of this team. I am delighted by the self-organisation of the team. It is great, particularity in a big firm!

 

According to your professional experience what are the most useful skills obtained during your degree ?

The most useful skill is my ability to learn quickly and to adapt myself to different environments. During the Master we have worked on applied and theoretical projects on a large variety of topics (marketing/bank/social network). With a background in Economics I quickly adapted to Engineering environment.

Moreover, I learnt a lot during my apprenticeship. One year of experience in a big firm allows you to be more efficient when you start. I already had very useful skills when I began to work for Airbus.

The Machine learning and programming courses are very useful to work in a firm. I used Python, R, RShiny and Dataiku. RShiny is a very useful tool, you can realise very sophisticated things!

 

What advice would you like to give to TSE or to the school?

Learn by yourself and be curious on different methods and ways of working! The world is changing all the time. I am always learning in the team and we have to be open-minded; everything can be useful for your career.

The involvement of professionals during the master was very useful. Having a strong relationship between the academic and professional worlds is key! For example, in the marketing course taught by P.Bizarri from Avisia, we used Dataiku DSS an analytics platform. It can make the difference in a CV!

One last advice: if you have the opportunity, go abroad!