Building the Best Data Science Team

Most businesses have decided to unlock the power of data and reap its benefits. The data available to them is vast and there is a constant lookout for experts who can comb through it, analyze it and convert it into real value for the business. Data scientists have become a crucial part of many organizations and the growing economy only keeps increasing the demand for them. Creating a good data science team can mark the beginning of success for your business goals.

Here are few things that you should keep in mind to build a data science dream team:

       1. Know your purpose

The first step is to figure out what your business aims to achieve and why it needs data science.  For instance, if your objective is to add some level of automation to your customer service processes, and make the responses more ‘human’ or intuitive, you need to hire a team of Machine Learning Experts rather than statisticians. A clear vision of what needs to be solved or achieved through your business will help you decide the type of data experts to be hired.

      2. Build one team with many skills:

To build a successful data science team, focus on assembling the right professionals with strong foundation skills and expertise in various aspects of data. The key is to get team members with a mix of different skills. Build a team with project managers, business analysts, data scientists, data engineers, data solutions architects, data platform administrators, full stack developers and designers, based on your requirement.

The team should have the ability to work on large and intricate data sets. It should also be capable of developing predictive models so that your company can have insight into what will happen next. A cross-functional team can definitely help you reach your goal faster and more efficiently.

      3. Know your platform

You need a solid infrastructure in place along with a strong team. While recruiting your team, consider the platform your company is using for the process. Hadoop is a pioneer in Big Data and it is the most common platform used today. Spark is also essential for real-time processing. Every team member should have the skills to use both these platforms. Those who don’t have knowledge about it can take up a relevant certification course. Understanding the fundamentals of Google Cloud and Excel can also give your business an added advantage.

       4. Accountability

It is important to decide where in the company chart your team will be located and who the stakeholders will be, depending on the mission, culture and resources of your business. This will prevent confusion in the future and avoid affecting the team’s performance.

       5. Use data to foresee your success

Data science has provided the world with endless tools that can analyze and measure the performance and requirements of the various aspects of a business. Use these tools for a predictive analysis on your data science team and measure them against your goals. Constant monitoring and reviewing can improve your team’s efficiency, performance and collaboration.

If your team is set on a course to achieve a collective goal, frequent reviews will ensure that good ideas are tested from different perspectives. This is one of the earliest signs of success.

It is always better to create a team rather than hire one ‘ideal person’. Take your time in choosing the right members based on their individual skills. Ensure they’re always keen on learning, which will have a long term impact on your business. They are ultimately the backbone of every major decision taken by the company and will determine the quality of your business.

Are there more steps involved in choosing the right data science team? Tell us in the comments.

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