In just two years, we’ve collected and processed nine times the same amount of information than the previous 92,000 years of humankind combined. Data is everywhere, and companies rely on well-trained professionals to process this unprecedented volume of information.
Data science workers need various technical capabilities to do their job effectively – including a solid understanding of Probabilities & Statistics, Linear Algebra, Python, SQL, and Machine Learning. Additionally, those who thrive in these roles have developed a wide range of soft skills, from critical thinking to problem-solving and business mindset.
We asked two data experts and teachers at Le Wagon Montréal, Lucas Nogueira, Scientific Analyst at McGill University, and Georges Bélanger, Applied Scientist at Microsoft, to tell us the most valuable skills needed to thrive in the industry.
Write Quality Code
“If you want to shine in a data science team, writing good code is golden”, according to Lucas.
You can use coding practice sites like Codewars’ kata to develop problem-solving skills. After finding the solution, you should refactor your code to make it as readable as possible.
If you’re not sure about what programming languages you should learn, start with Python. It’s the most popular language for data science and has a very elegant syntax.
Learn Cloud Computing
If you’re looking to break into the data market, getting cloud skills should be on top of your list.
Cloud infrastructure allows companies to store data and train machine learning models without owning their own infrastructure or data centers. Nowadays, data science and cloud computing go hand in hand. Because it makes it easier to deploy data solutions, prospective data scientists should be familiar with at least one public cloud like AWS, Google Cloud, or Microsoft Azure.
Use Your Previous Experience To Your Advantage
If you want to differentiate yourself on the job market, you should use your previous experience to your advantage. “Who better to become a data scientist in the construction industry than a civil engineer who used to work in this field? We need subject matter experts on the data market”, says Lucas.
There are more and more graduates with PhDs and Master’s degrees in data science and artificial intelligence. While they have a solid theoretical background in mathematics and data science, they might lack business skills. If you have experience outside of the data science field, you should use it to differentiate yourself!
Develop Business Skills
A data scientist mainly deals with business issues, so it’s essential to have a strong understanding of the business and industry you’re working in.
Those who thrive in the data industry are the ones who understand what data can be used for and how it can improve business decision-making.
Additionally, communicating clearly about your work – with your team and customers – will give you an advantage in the industry. According to Lucas, “It’s crucial to know how to tell a story and break down complex concepts into a way everyone can understand.”
Build A Portfolio
Portfolios are not only for designers! The ability to show employers what you’re capable of doing is crucial. This is especially true if you’re starting your career and don’t have any work experience yet.
To find project ideas, you can explore Kaggle’s datasets. Doing some web scraping is also an excellent way to find interesting data to play with. If you want to know more about exploring and using datasets, you can join Le Wagon’s upcoming free workshop about data analytics.
Adopt A Growth Mindset
Finally, Georges Bélanger believes that the most critical skill is cultivating a growth mindset, meaning that you should stay curious and never be afraid of not knowing something.
“Instead of trying to look smart, you should always be asking questions and be curious. When you’re unsure about something, ask questions and look for feedback! That’s how you’ll grow as a data scientist.”
Soft skills are as necessary as technical skills to thrive in the data industry. If you’re interested in getting into the field, have a look at Le Wagon’s Data Science bootcamp. Our programs are based on the latest data technologies to teach students how to build real-world data applications while adopting the technical workflow of successful tech companies.
Ines Alvergne is the Marketing Lead at Le Wagon.