Turing College Senior Team Leads on how to get hired and get ahead in data science

Turing College Senior Team Leads on how to get hired and get ahead in data science

In a previous article, 3 Senior Team Leads shared some insights on their role at Turing College and some tips on what it takes to successfully complete your studies with us. But what about life beyond that? Data science professionals Adomas, Lukas and Deividas are back to tell us more about the skills and qualities you'll need for a successful career in data science.

First up, here's a quick reminder of who they are:

  • Adomas Lingevičius is a Data Scientist at green energy trading platform WePower.
  • Lukas Buteliauskas, is a Data Scientist at goHenry, fintech that helps kids learn how to manage their money.
  • And Deividas Skiparis is a Machine Learning Engineer at Vinted, an international online marketplace for pre-loved clothes.

And, of course, all 3 of them are Senior Team Leads at Turing College. They provide learners with the feedback and support they need to progress through our course and beyond.

Adomas, Lukas and Deividas are data science professionals at top tech companies, and Senior Team Leads at Turing College.

Starting out in your first data science role

When you graduate from Turing College, we help to match you with one of our Hiring Partners to kick off (or accelerate) your data science career. In fact, our whole mission is to ensure you land a great, well-paid job once you've completed your studies with us.

But what will your first job in Data Science look like?

The first point to understand, says Lukas, is that the requirements may vary a lot depending on the company you end up working in. "The field of Data in general is quite new," he explains, "and Data Science sits at the top of the hierarchy of AI / data maturity within an organisation."

This means the roles you need to perform as a data scientist will depend a lot on the maturity of the company. "Companies first need to build the data infrastructure (data engineering), and then they need to be able to answer questions and dig into it. So companies should only start looking for data scientists when these initial needs are met. However, this isn't always how it works. If the company hasn't reached maturity in terms of its data engineering and analysis, you'll need to help with these responsibilities first."

So, a flexible approach to your first data science role is definitely important. Nevertheless, there are clearly some fundamental hard and soft skills that companies will be looking for in their data science hires.

Key hard skills companies are looking for from data scientists

Deividas says companies recruiting junior engineers will expect them to be able to "analyse datasets, derive useful insights, and help teams to make data-driven decisions." He also believes companies will want "enough knowledge of Machine Learning to build, evaluate, deploy and test Machine Learning models in production."

And Lukas offers a handy checklist of important hard skills that are necessary for most data science positions:

  • "proficiency in Python and its Data Science stack (pandas, numpy, matplotlib/seaborn, scipy, skLearn to name a few),
  • knowledge of either SQL or Spark/pySpark,
  • And knowledge of Machine Learning."

He points out that "Deep Learning is not typically required, but this will depend on the nature of what the business does."

Key soft skills companies are looking for from data scientists

Turing College doesn't only teach the hard skills data scientists need. By replicating the way real IT teams work, it also develops important soft skills that employers are looking for. But what exactly are these skills?

Adomas argues the most important soft skills a data scientist needs is "the ability to translate your knowledge and findings in a way that your fellow data scientists and managers can understand." Lukas agrees, emphasising the importance of "being able to communicate to a technical and non technical audience."

Deividas focuses more on attitude and outlook. "In my opinion, the 2 most important soft skills for a data scientist are the ability to learn and perseverance. If you can deliver work, are prepared to fail to succeed, and can drive your own learning - you should have no problem getting hired," Deividas states.

For Lukas, alongside communication skills, data scientists should also have "the ability to problem solve, a passion for learning, curiosity, and a "self-starter mentality."

STLs offering real-work advice

How to give feedback, how to learn successfully, key skills you'll need in the workplace: the STLs at Turing College have valuable insights on a wide range of topics, as this article demonstrates.

And that's exactly why they have an integral role in the Turing College set up. They are there to give valuable real life advice, along with technical expertise. And this gives Turing College learners a competitive advantage over their peers.

As Adomas explains, at Turing College "you get structured studies with regular assessment, which allows you to understand where you are in terms of your learning journey. And there is a close-knit community - your fellow learners, the staff and the STLs."

And this community gives you the support to flourish.