Data science is a growing field at the moment. Many businesses, even those outside the tech sector, have realised that utilising the discipline can improve a business’s bottom line. As such, data science employees are in high demand. But, within the data science industry, what do employers look for?
We’ve already found some of the top companies hiring right now, but now we have to ask, ‘what do employers look for in data science candidates?’
The answer, it turns out, depends very much on the specific company and the specific role.
What employers want – passion and innovation
Of course, there are some universal themes. Of the data science employers we spoke to, the majority espoused the virtues of being passionate and innovative.
“The best performers love what they are doing, so a passion for technology and positive attitude will go a long way,” says Dave Kiely, software development manager at AOL.
For AOL, teamwork and cultural fit are also hugely important. They want to know that their employees will work well together.
“Good interpersonal skills can be the difference between an average employee and a rock star,” says Kiely.
In addition to a “passion for data”, Tableau Software see the benefit of having employees with an “ability to think out of the box,” according to Giulio Calef, senior manager of technical support at Tableau.
Of course, as Tableau is so data driven – it’s the core of their business – employees really need to be able to “grasp the essential phenomenon which lies behind the data, and use data visualisations to bring it in front of the intended audience,” continues Calef.
Pramerica looks for candidates who enjoy innovation and collaboration.
Leeanne Mimnagh, human resources director at Pramerica, says, “We look for people who can help us find innovative business solutions, and can adhere to our commitment
The company also likes its employees to aspire to an ‘own your career’ philosophy, so if personal development and empowerment is your thing, Pramerica is probably the place to be.
Colm Molloy, human resources director at Storm Technology, speaks about Storm’s focus on “high-energy, innovative thinkers” with “a drive to succeed”.
Teamwork is also hugely important at Storm, as “most of our work is team-based”.
At Fidelity Investments, the onus is on long-term perspective. Says Linda Devenney, director of data architecture at Fidelity, the financial services company seeks “people who are willing to embrace our culture of long-term vision and who are going to stay and grow their careers with the organisation”.
Bright, ambitious individuals with a desire to apply their skills in innovative and creative ways will go far.
The niche skills
Have you ever not gotten a job after doing a killer interview? Perhaps you wondered afterwards whether the employer was looking for something specific that you just didn’t have.
You may not be too far off the mark.
Many employers have a specific skill in mind that will make a candidate stand out for them.
For Tableau, it stretches beyond IT and coding skills, though those are hugely important. “Curiosity to dig deeper and tell a story,” says Calef, is something that will immediately set a potential employee apart from other interviewees.
Teamwork and interpersonal skills are also highly prized, Calef continues: “Two of our core values are ‘we work as a team’ and ‘we respect each other’, and we live to those each and every day.”
AOL looks for different skills depending on the role – an understanding of programming, statistics, machine learning and datavis for data scientists and data analysts; databases, Hadoop, Spark, and programming languages like Java and Python for data engineers.
That’s not all they look for, though.
“I have seen many new hires start and think their job will only consist of coding in one language and on one project,” says Kiely. “In reality, our engineers can code in multiple languages and must be flexible to work across projects and timezones.”
As such, flexibility is highly prized at AOL.
At Storm they seek candidates with a collaborative personality. According to Molloy, “an understanding that all levels get involved and that the team is the winner” is essential.
Fidelity looks for candidates with an interest in expanding their minds – “through this willingness to learn,” says Devenney, “our employees create the best user experience for our customers”.
For Pramerica, it’s about diversity, but not in the way you think (although having a diverse staff is important to them, too) – it’s about diversity of skills.
“More and more these days it is not enough to be strong in just one skill set,” says Mimnagh. “For example, this year we were looking for candidates for an actuarial position who had programming experience in addition to typical actuarial skills. And a successful candidate for a data science jobs must be able to communicate and influence the business, in addition to having strong technical and quantitative skills.”
The way in
Now that you know who’s hiring, and what they’re looking for, all you need is a way in.
Firstly, it’s important to note that most employers will be willing to hire people without a direct background in data science.
Not all roles within the industry are ‘data science roles’, with a bevy of tech-adjacent positions available in most companies.
Furthermore, for the data science-specific jobs, many tech employers offer extensive upskilling courses for new employees.
According to Mimnagh, “In the field of data science, you can never stop learning, so [Pramerica] continuously runs a mixture of hands-on practical training and classroom-based training to upskill newly hired employees, as well as existing team members”.
At Fidelity, says Devenney, “we believe that we can augment existing skills through training.”
Leveraging Tableau power to help people see and understand data is key at Tableau, and new hires undergo training in that area. “We have robust new-hire learning paths in all roles,” says Calef, “so catching up with others is not a problem”.
According to Kiely, AOL provides training on an ongoing basis, offering externally- and internally-taught sessions on a range of skill areas in order to “ensure our engineering resources can meet the needs of the business”.
At Storm, “There would be some technical development, but we work closely with our partners [Microsoft] to upskill anyone with a shortfall,” says Molloy.
Paths to data science
‘Of course, it’s all well and good for experienced data scientists’, I hear you say. ‘There are lots of opportunities for them. But what about those of us who are just starting out?’
You haven’t been forgotten.
In addition to the wealth of positions for those experienced in data science, many employers offer graduate and intern programmes.
Storm, for example, offers a focused graduate programme and works closely with colleges to provide internships – often leading to full-time, permanent roles – for final year students.
Pramerica has an annual data science internship programme, which focuses on current students and recent grads who want careers in data science. “The programme is developed to give the perfect blend of real data science work mixed with practical training from senior data scientists,” says Mimnagh.
Fidelity provides paid internships, and interns often convert to the graduate programme, Leap. From there, it’s a short step to full-time employment within the company.
At AOL, internship and graduate programmes are a stepping stone into the industry.
While Tableau does not currently offer grad or intern programmes, “we are looking at possibilities to start a programme in the near future, and are working with local universities in that respect”.
So now you know what data science employers want, there’s only one thing left to do… apply!
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