Building A Rock Star Data Science Team


Organizations today need to do a lot more than just acknowledging big data. Today, they need to make data and analytics an integral part of their business. Obviously, this will need building a quality data science team to handle the data and analytics for the organization. Choosing the right team members can be difficult, primarily because the field is new and most companies are still trying to identify exactly what a good data scientist should be able to do. The following information should help to make the process simpler.

The Right People

You will need to have data scientists who can work on massive datasets and who know the theory behind the science. Moreover, they should be capable of building predictive models. Data software developers and Data Engineers are significant, too. They need to understand the infrastructure, architecture, and distributed programming.

Some of the other positions to fill in a data science team consist of the data platform administrator, data solutions architect, full-stack developer, and designer. Those organizations that have teams focusing on developing data products will also possibly want to have a product manager. If you have a team with a lot of skill but is low on practical experience, you may also need to have a project manager on the team. It can help to keep the team on the right track.

The Right Processes

The primary thing to keep in mind when it comes to the processes is agility. The team should be able to access data in real time. It is essential to do much more than just to measure the data. The team requires taking the data and comprehending how it can affect different areas of the organization and help those areas implement positive changes. They should not be chained to a slow and dreary process, as this will limit efficiency. Ideally, the team should have a good working relationship with the heads of other departments, so they work together actively in multi-disciplinary teams to make the optimum use of the data gathered.

The Platform

When building a data science team, it is also essential to consider the platform your organization is using for the process. A variety of options are available including Spark and Hadoop. Hadoop is the most important tools when it comes to big data technology, and it is a necessary skill for all professionals who get into the data science field. Spark is becoming increasingly important when it comes to real-time processing. Therefore, it is a good idea to have all the big data team members skilled with Spark, too.

If you have members of the team who do not have these skills and who do not know how to use various big data platforms, it is essential they learn. Corporate training in data science can be an excellent option for teaching the additional skills needed, and to get everyone on the team on the same page.

Location: Bengaluru, Karnataka, India

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