Data science is all the talk right now, and for good reason. Not only will it help you streamline your business processes, but it will also put you on track for greater success and profitability. However, it may seem a bit overwhelming at first glance. What is the best way to tackle this as a business manager or owner? Can you handle this task on your own? Let’s take a look at four tips to build a top data science team.
1. Understand the Importance of Data Science
Before building your team, it’s vital to realize how your business can benefit from data science. You most likely have a good deal of data already collected and saved, waiting to be cleaned, mined, and analyzed. With the proper analysis, you can achieve the following:
- More efficient operations.
- Better decision-making.
- Enhanced customer relations.
- Boost in marketing efforts.
- Reduction in time wasted.
It’s vital to have a data science team to gather the information and generate reports so you can accomplish these goals.
2. Start With the Basics
Since the process of data science involves several steps, you want to ensure you have a solid team in place, but that doesn’t mean you need to hire a whole new team. You can start with just the basics, such as:
Data Engineer
A data engineer is one of the foundational people in a data science team. They will work with the raw data, collecting, preparing, and managing it for others. They may also be involved with creating, testing, and maintaining the data to ensure data quality.
Data analyst
A data analyst is an instrumental part of the team because they make sense of the raw data. They use statistics and understand algorithms to interpret the data. This helps the business understand what the data means to them and how they should move forward.
Data Architect
The duties of a data architect consist of designing, overseeing, and managing the data infrastructure that the team uses.
3. Don’t Focus on Specialists
When determining who should do these jobs, or when hiring for these jobs, keep in mind that these individuals don’t necessarily have to be specialists. In fact, hiring someone with the necessary skills across the board, along with a strong set of general data knowledge, might be better. That way, they may be able to juggle a few tasks at once.
If their skill set is too specific, they might not be able to do other tasks. Since you’re just starting out, you probably want to minimize the number of individuals you have in highly specific jobs to reduce costs.
4. Keep Accountable
After you’ve assembled your team, set a timeframe for when you’ll meet so they can provide you with deliverables. You could have meetings at regular intervals – whatever timeframe works best for you — whatever works best. Have the team prepare a report using visuals to see the progress the team is making. This helps keep them accountable and lets them show off their wins.
Find out more about building a data science team today! Your business will benefit from a partnership of talented individuals collaborating to compile, study, and utilize data.
Also read: Top Abilities of A Data Scientist and How to Improve Them
