Jobs in the tech sector, such as data scientist, can be hard to understand and that’s why we decided to ‘decode’ them by chatting to our colleagues at the Rakuten Group, often called Rakutenians, via a regular blog column called: Decoding technical jobs.
We’re very pleased to have an opportunity to leverage the enormous depth of technical talent that we have in the group in order to inspire, encourage young generations but also boost diversity in our sector. And today we’re discovering what it means to be a Data Scientist as we are talking to Michael Cohen, from Rakuten Marketing France.
Head of Data Science : Michael Cohen
Hello Michael! Thanks for taking part.
Tell us about being a Data Scientist
Data Scientists are the Machine Learning experts. It’s a thrilling, modern and quickly changing job that is impacting every single industry, from marketing to health services or automobile industry. Data Scientists use advanced algorithms in order to either find hidden correlations between key variables – thus answering a question such as “what is the mathematical relation between A and B?” – or to automate human decisions with an automated learning process, meaning the machine will get better with time and as new data examples appear. In both cases, the finality is to be able to make accurate predictions about the future using the data from the past.
What’s your typical daily task?
The Data Scientist’s tasks are various. It goes from extracting your data to writing model prototypes or designing new platform functionalities. But the two main tasks are the research, that is, reading scientific papers to understand the best-performing algorithms available, and the algorithm implementation with languages such as Python, Scala or Java and using Big Data Framework such as Spark.
What’s exciting about your job?
Data Scientist is one of the rare jobs where you can both apply your math skills in the industry and mix them with the newest technologies. Being a Data Scientist also requires that you understand your product. So it’s a marvelous mix between maths, code and product design.
What’s most difficult?
The most difficult is probably that, since Data Scientist is a relatively new job, we have to be very good at explaining what it is really about and what it can – and cannot – accomplish. Non-data scientists have a vision of data science that ranges between the black box and the magic engine that will change any data into gold (!) So an additional challenge for us is to be precise in our explanations and to be able to describe our algorithms in a way that helps our colleagues visualize what the inner mechanisms and results will be.
What kind of training and skills you need to become Data Scientist?
Ideally, a Data Scientist has a strong background in mathematics and statistics and has followed an academic program oriented around Machine Learning or Computer Science. A Master’s level is often required. The combination of mathematics and coding is what makes the specificity of these profiles.
How do you think your job will evolve in the future?
Data Scientist is a young job, and the tools are really quickly changing. I think that very soon companies will realize that Data Scientists should not only be good at working ready-to-use tools, technologies and libraries, but also at designing and customizing the algorithms and pipelines in order to specifically fit their business.
What makes a Data Scientist laugh?
Images speak louder than words!
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