In the world of data science, it’s not uncommon for a team to contain ten to fifteen people. I’ve worked with teams consisting of seven to ten people, and even with the latter size, it’s still a highly collaborative environment. It really requires a lot of communication and collaboration in order to get the job done.
Data science teams really do have to communicate, because a lot of the time, the data on a project isn’t that clear-cut. When an idea or question is made public, it can quickly become complicated and require a lot of work to “get it.” Sometimes this leads to a team member getting a bit too busy with the task at hand, leaving a project that they should have been working on for weeks, if not months.
You see this all the time in data science. Sometimes the best way to make sure your team is working on a project efficiently is to have your own data and to share it. I know it sucks not to have a perfect idea, but there are a ton of ways to make sure that your team is learning how to work with data.
I’ve been playing around with a few different ways to use data for awhile. One of the most popular ways is the “data science team” model. In this model, the project manager gets a list of “top 100 projects” that a given team member has been assigned to, and that person is supposed to be the one who is going to give the data to the team. This can work well if the team is a small one, but it’s not really scalable.
This is a very useful way to start your data science team, but you’ve gotta have a way to communicate what the project is in the first place. For that you need a data plan. A data plan is a list of all the data you have that you need to work with. You should include the data in your presentation, but do not make it too long. In my case, it only has enough data for me to create a chart.
Data plans often include a project plan and a budget. A project plan is what the team needs to know how to do their job. A budget is what the team needs to know how to spend their budget. The most important thing to remember is that you can’t have a project plan without a budget. A budget is like a spreadsheet with all the numbers you need to know. You should include the budget in your presentation too, but don’t make it too long.
It sounds a little scary, but it’s actually quite simple to create a project plan and budget for a data science team. All you need to do is create a spreadsheet with all the data you need to know. I usually do this in PowerPoint or Excel. You can add any data you need to your spreadsheet in the spreadsheet itself, but it’s a good idea to include the budgets in the presentation as well.
The thing about a data science team is that you can quickly set up a budget and project plan for your team to work from. This gives them a clear idea of what they can and cant do, and how much time and money they can spend on the project. Once you have that out of the way, it’s the time to get the rest of your team involved and show them what you have.
There are two ways to do this. The first (and most elegant) is to show them the spreadsheet and then let them work it out themselves. The other is to give them an overview of what you have and then have them work it out. In either case, you want them to have an idea of the budget and what it tells you about what your team can and cant do. You can use a spreadsheet to keep track of what your team has done.
If you’re looking to make your team feel like part of the team, you need to give them a sense of what they’re contributing. The spreadsheet approach is one that many people use here at Sploid. Another common way to do this is to get them to give you a written project that describes what they’re doing and what their schedule is.
