Looking for new employees, particularly in the data science space, can become a time-consuming task. Most companies are looking for specific skills in their next data-based hire; however, it can feel impossible to find someone with every skill you might need.

Without the right knowledge or research, your organization might end up investing time, money and energy into a traditional hiring process — without much to show for it. You might spend weeks, sometimes longer, conducting interviews and reviewing dozens of candidates. When one or more candidates are finally hired, you’ll have to meet their salary requirements, benefits package, and any other bonuses, equity, or compensation required to onboard them.

Today, many of the best data-driven companies are choosing to hire apprentices >over> traditional data employees, to help businesses subsidize their workforce.

What is a data science apprenticeship program?

Data science apprenticeships are paid educational programs that combine learning with real-world data experience. They allow aspiring data science professionals to learn fundamental data science skills without enduring a traditional degree program. Apprenticeships are certified to ensure they meet industry standards, meaning that apprentices can use their skill sets for any company which hires them to fulfill data science requirements.

Some employers will confuse apprenticeships with internships, believing apprentices are temporary employees. This is untrue. Apprenticeship programs are not unpaid, unstructured or temporary.

Instead, they help employers:

• Access pre-trained, diversely talented learners
• Build a talented, data-heavy workforce
• Sustain 30-40% cost savings over traditionally-sourced talent
• Yield higher employee retention rates

Data science apprenticeship programs are created specifically to foster successful, long-term professional rel

As your business begins to scale, you may find yourself in need of additional data science resources, and team members. This isn’t always an easy process — how do you know who to trust with your company’s information and network? And how can you be sure that they will be the right fit for your organization?

In this article, we’ll outline best practices for hiring the right data science team to complement your operations. We'll also help you understand what to look for, and how to make sure that your new data science team can help contribute to your overall goals.

Why do I need a data science team?

The first step in hiring a data science team is to identify your internal data-related needs. Do you need someone to manage your company’s data? Do you need help with migrating your information from one data collection platform to another? Do you also need help in collecting that data, or in applying strategies that help you derive meaningful conclusions from the data you collect?

Do you need a specialist, or specialists, who can manage or optimize, your entire data science process for you?

If you're expanding your business, changing your business model, or simply attempting to learn more from your business practices or customer behaviors, you might need a more hands-on approach to data science. And if you’re not sure where to turn for your data science needs, you might need a data science partner that can help diagnose your data needs before helping to satisfy them.

Understanding your data science needs will help you identify the right team members for the job.

How do I form the right data science team?

Let's talk about how to form a data science workforce that improves your organization’s use of the information you collect.

When determining which type of data science team you’re assembling, there are a few important steps to keep in mind.

1. Identify your data science needs

Before