In today’s data-driven world, the ability to hire and retain top talent is crucial for any organization that wants to stay ahead of the curve. This is especially true in the field of data science, where the demand for skilled professionals continues to outpace supply. Yet, despite the importance of hiring, there is often a disconnect between data leaders and recruitment heads that can lead to missed opportunities, miscommunication, and frustration.
To explore this issue, AIM Recruits hosted a roundtable discussion at the Machine Learning Developer Summit 2023 on “Bridging the gap between Data leaders and Recruitment Heads”. The panel included data leaders from the AIM Leaders Council and recruitment heads from various industries. Their insights shed light on the reasons for the gap and provided practical tips for bridging it.
The Challenges of Hiring for Data Roles
One of the main challenges of hiring for data roles is the diversity of skills and experience that are required. As Ravindra Patil, Group Leader, Data and AI at Philips, pointed out, “We’ve been setting up teams with three separate job descriptions like data scientists, data engineers, and data analysts. So, when the resume comes, it’s quite mixed. While at a CV level, it’s hard to differentiate because the boundaries are also merging somewhere.”
Moreover, the ever-evolving nature of data science and the rapid pace of technological change can make it difficult for recruiters to keep up. As Mohit Juneja, HR Leader – Engineering and Technology Centre & Org Capability – MEIA at Ingersoll Rand, noted, “Without upskilling, you will not see good outcomes.”
On the other hand, data leaders often struggle to communicate their needs and expectations to recruiters. “I think it’s very important for recruiters to also understand the culture of each department that they’re catering to,” said Rosina Jose, Associate Director HR at Rakuten India. “We need multiple training sessions for that to ensure that not just tech but even this side of things are taken care of.”
The Importance of Communication and Collaboration
To bridge the gap between data leaders and recruitment heads, the panelists emphasized the need for better communication and collaboration. “What is critical is the conversation that is happening between a data leader and an HR leader, when it is not a recruitment conversation,” said Sayandeb Banerjee, Co-founder and CEO at TheMathCompany. “There is a way to explain in a layman’s language, what this is about and the same holds the other way around that the data leader takes ownership of the talent they need to build the product and solution.”
One way to improve communication is to involve both data leaders and recruitment heads in the decision-making process. “We need to come together as a community and have a uniform definition of what is data science, who is a data engineer, because for every organisation, the definition changes,” said Lijosh Varkey Joseph, Director – Talent & Culture at Flutura Decision Science & Analytics.
Another way to bridge the gap is to provide training and development opportunities for both data leaders and recruitment heads to learn about each other’s roles and responsibilities. “The fundamentals of having a good hiring strategy meeting, good job description in place, and a well-defined tool come in place, which help the candidate understand what the role is,” said Patil.
Conclusion: Moving Forward Together
Bridging the gap between data leaders and recruitment heads is not easy, but it is essential for any organization that wants to stay competitive and make data-driven decisions. By improving communication, collaboration, and understanding of each other’s roles, companies can achieve a better outcome.
As Shan Duggatimatad, Data & AI leader – Senior Director at Ascendion, highlighted in the roundtable discussion, it’s important for recruiters to look beyond technical skills and focus on softer attributes when assessing potential candidates. While some skills may be in-depth and require a technical recruiter, recruiters should also look for broader and horizontal experience and emphasize softer aspects such as cultural fit and communication skills. By doing so, recruiters can help identify candidates who not only have the necessary technical skills but also the interpersonal skills required to work effectively in a data-driven environment.
