How to become a data scientist

Become a data scientist

How to become a data scientist? Cannelle is a young engineer graduated from Polytech Nice-Sophia, she is passionate about data processing issues in a Big Data environment. She introduces to us her career path, her job as a data scientist and tell us about her own experience at AViSTO.

AViSTO is hiring data scientists. You can find our employment opportunities on our website, or get the opportunity to submit a spontaneous application.

Data Scientist vs Data Analyst

In the big data world, are you a data scientist or a data analyst?

My profession is quite recent, there is none fixed definition yet. In my opinion, the data analyst is someone who is mainly in charge of the data analysis whereas the data scientist is also responsible of the study and algorithm parts. So, I define myself as a data scientist, but it’s only my interpretation !

Data Scientist Educational Background

Can you introduce your career path which enabled you to become a data scientist?

I am graduated from Polytech Nice-Sophia, in the Mathematics applied and modelling stream. I specialized myself on the second year of my Master degree in the Big Data processing. This formation in mathematics and informatics allowed me to combine theory and practice in order to grasp complex issues more effeciency.

Roles & Responsibilities

More specifically, what is your job as a data scientist?

I believe that the data scientist has to be versatile and multi-skilled in differents aspects. For instance:

  • The functional side, to appreciate the client job, his activity. This is necessary to understand the data, to use it and to represent it.
  • The study aspect, in order to develop adapted mathematical algorithm. To that end, we read scientific papers, or we create it ourselves.
  • The development aspect: once the algorithm is conceived, we have to code it in an appropriate programming language. Usually, in the business world, we use the Python language. In the research area, the R language is commonly used.

After the algorithm encoding, it is included in a data processing software which is often the one that the company uses. But we can also check if it doesn’t exist a software more suitable to the studied data.
Then, in the big data sector, we have to take into consideration the distributed processing issue, or parallelism. There is an increasing number of calculations made on Small-Scale Servers today and no longer on a single big server.

Big Data is a hot topic. How do you catch up on the latest developments?

I watch over on technological and algorithmic topics. My process is not very formalised, I let myself be guided by my intuition and my interest. At the begining of the year for instance, AlpaGo and its learning machine algorithm trumped the world champion Go. When I heard about it, I look upon the Internet to understand how it works.
I also go to conferences, such as Riviera Dev in Sophia Antipolis (an event sponsored by AViSTO).
But there is so much innovations that it is impossible to watch all of them, so I remain regularly informed of the latest released technologies.

Why she loves her job as a data scientist

What do you like in your job as a data scientist?

I love to turn the raw data into something exploitable, to produce something concrete so that the human being is able to understand it. I love to use mathematics processing (algorithms, etc), or new distributed processing data frameworks (ex : Hadoop, Spark) to transcribe the data.
I really like the real-time challenge, where the algorithms are designed to be lighter and more usable.
In brief, what I love about my job is linking the information and mathematics to produce some value.

Why did you decide to become a data scientist?

I am at ease in mathematics since I began studying it. I discovered computer science in my engineering school and I enjoyed it. This is why I wanted to found a job that would enable me to do both.
Moreover, I have always been interested in creativity and innovation: we can manipulate data in very differents ways which requires some creativity and an innovative state of mind.

And how did you do to find this profession?

I first discovered the data processing thanks to pictures processing internships, including at Wildmoka, a Sophia-Antipolis start-up. The image processing is an application field of the data processing. That is how I get to data science.

Her experience at AViSTO

Can you tell us more about your experience at AViSTO?

Thanks to AViSTO, I have the chance to work with emerging actors in a challenging context. I deal with issues about data event, which implies real-time treatment.
More than that, AViSTO allows me to stay informed of the latest innovations, by proposing formations such as the Cassandra Developer certification from Datastax, or by supporting the participation to the conferences of the Sophia Antipolis technopole regarding the innovations and new technologies (Riviera Dev for example).
I am very grateful to AViSTO for everything, especially Jean-François, my Business Manager with whom I get along quite well.

Projects examples:

  • Implementing of a « from scratch » Business Intelligence solution to exploit data from shops in an international airport.
  • Implementing of a big data solution – business intelligence allowing the data analysis of an electronics vehicules park from a big company.

Data Scientist Employment

AViSTO is hiring data scientists! You can check our employment opportunities on our website, but also submit a spontaneous application.

A big thank you to Cannelle for her testimonial!