Data Science Roles are the Future: Here’s How to Hire for Them

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Being a “data driven” company isn’t just a business buzzword, it’s a necessity. Companies are increasingly reliant on data to make key decisions across nearly every team and every level: from product development to engineering to marketing campaigns and community building to the c-suite. Without reliable access to data companies are flying blind about their operations and opportunities. As such, they are increasingly reliant on data teams, including data scientists and data engineers, for success. 

Data drives companies at all levels

Data-related occupations are growing rapidly: According the the U.S. Bureau of Labor Statistics the data science field will expand about 28% through 2026, resulting in over 50,000 new jobs. 

This rapid growth is a testament to how data informs the ways we work and make decisions. As such, data scientists, and the ways they collect, analyze, and present data must be integrated into a company’s systems and processes. Data professionals need to understand how data systems interact with a company’s product and software stack and speak the language of engineering, product development, and leadership. Data scientists are translators of information and help bring clarity to ambiguous situations. 

The hybrid roles of the future 

Because data is critical at all levels for a company’s success, a modern data professional requires a unique blend of skills to succeed. The role of a data scientist or data engineer is integrated, not siloed. A data professional serving a modern company must not only understand how to collect, analyze, and present data, but also be a master of creative thinking, problem solving, and diplomacy. These professionals occupy a hybrid, cross-functional role whose overall goal is to drive business value. 

In their 2021 data and analytics trends report, Gartner reports that data teams serve a core function in their companies. The goal of these teams is to enable companies to “achieve efficiencies and economies of scale” and “ensure reliability, reusability and repeatability while reducing the duplication of technology and processes and enabling automation” so that companies can operationalize data and be more efficient. 

How to hire for hard-to-hire data and engineering roles 

“There are very few data scientists out there passing out their resumes,” LinkedIn co-founder Allen Blue said in a paper for the Wharton School,  “Data scientists are almost all already employed, because they’re so much in demand.” Because data professionals occupy a true hybrid role — between engineering, product, business leadership, and the data itself — candidates may possess some, but not all of the skills a company desires. In addition, emotional intelligence and the ability to collaborate and communicate across teams is crucial. As companies compete for these hard-to-fill roles, it’s important to consider a range of strategies for filling the hiring pipeline.

Instead of spending valuable company resources on sourcing, recruiting, and trying to woo a “unicorn” employee, companies can consider offering on-the-job training through an apprenticeship program to prospective and existing employees. These are candidates who already have a baseline of skills, a willingness to learn, and would be an asset to a company’s culture. Investing in them through an apprenticeship program is a sustainable solution that enables promising employees and candidates to develop the specific skills they need to succeed in your company’s hybrid roles. And data scientists can come from a wide range of professional and academic backgrounds. Tsvi Gal, CTO of infrastructure at Morgan Stanley who runs a data science training program there, told the Wharton School that some of their most successful participants are liberal arts graduates in addition to those with STEM experience.

Apprenticeships can also help diversify the field of data science, which is currently dominated by men, and give broader opportunities for professional advancement in technical roles for candidates and employees from underrepresented backgrounds.  

At Onramp, we work with companies like Twitch to develop rigorous data science and engineering apprenticeships that give candidates the skills and support they need to succeed in these hybrid roles. Reach out to us today to learn about how we can work with your company to design an apprenticeship program that increases your hiring velocity and helps you fill your hardest-to-fill roles. 

Applications are now open for the Twitch Data Science Apprenticeship! APPLY NOW. Applications close 5/24. 

Written by
Odette Nemes

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