What skills are important in data scientist roles?
Most of us think that being a data scientist is a pretty left-brained role. A data scientist should be good at working with large datasets and performing complex analysis on them.
Maybe you even think that there is no room for being artistic and using your imagination in that job. But if you’re like us here at Partners in Company, you understand that a good data scientist is also creative.
For us, creativity shows up in three ways for a data scientist: methodology, presentation, and visualization.
Methodology: Choosing an approach
Choosing the right approach when analyzing data, is definitely an art in and of itself. Say we want to predict how customers purchase a certain product. One straightforward approach is dividing the customers into two groups, those who purchase and those who don’t (called a classification model). Another approach is to bring into the equation variables that influence the purchase decision like price, features, timing and product placement. In your data scientist role, it is important that you are flexible and creative in using your analytic approach (such as identifying specific variables) because not all problems are created equally, therefore you need to customize your approach towards the problem and not the other way around.
2. Presentation: Delivering the results
Delivering results is a lot like storytelling; once you have identified a problem, you need to build a story around it. A simple framework to follow is; Introduce the problem, Quantify the Impact, Propose a Solution, Again Quantify the Impact and Describe Effects of Alternative Solutions. This is usually an area that requires the most creativity in data science. Communicating results effectively, in a manner that is understood by all, is an important part of your role as a data scientist.
3. Visualization: Making your data more understandable
This one is a given. Every time we make a graph or dashboard more aesthetically appealing, we pull our creative side out and influence the data scientist in us. We experiment with different charts and graphs until we find one that best delivers our message. We recommend that you try to understand the audience and situation before beginning to visualize the data - this way you avoid the possibility of having confusing visualizations that don’t fit well with the context.
Feel like your creative juices aren’t flowing? Don’t worry, Rome wasn’t built in a day and creativity doesn’t just happen overnight. Here are some ways that you can start harvesting your creativity:
Read More
Read about how firms are implementing analytics, statistics, and AI. Read the newspaper about firm initiatives and experiences with data. Read different case studies and understand the approach companies have taken to solve their problems.
Dabble in Art
Dance, paint, join an improv class - whatever form works for you. A big part of creativity is simply seeing differently and one way to do that is to get your hands directly involved with art.
Volunteer
Volunteer for something that is outside your comfort zone. This way you can meet a diverse group of people and get a new perspective on the world. Practice empathizing with groups that are different from you.
In conclusion, data science is an art in itself. As a data scientist, you have to constantly be thinking of creative ways to answer questions about your company and present the results to your coworkers. You have to decide about the vizulations and presentations that tell your data story.
And if you feel that you’re not creative enough, then we suggest reading about different approaches from real-world examples, taking an art class or stepping out of your comfort zone and volunteering. Simply try things that help you see the world differently.