The Gorilla Glue Company, Sr. Director of Data Science: Robust and Repeatable Data Reporting Improves Business Strategizing
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(US and Canada) Michael C. Fillios, Founder and CEO of IT Ally, talks to Kelly TeDesco, Sr. Director of Data Science, The Gorilla Glue Company, about her experience thus far in executing her data leadership role — a new position in the company.
TeDesco’s initial task has been meeting with colleagues to understand the business and how it’s using data today. For example, what types of questions are they answering with data? What unanswered questions remain? She is brainstorming how data science can help The Gorilla Glue Company improve strategizing, and she has a list of media projects that will help develop a year-long roadmap.
TeDesco explains that data science improves business decision making. To be effective, however, a data scientist must first understand how a company will use its data in the future. In this way, they can affect real change rather than just gathering interesting insights. Secondly, she continues, a company needs a data science platform, but trying to understand the technology options available can often be overwhelming to define. “There is so much out there and so many choices. So, the companies at the beginning of a data and analytics journey must start with robust and repeatable reporting if it is not already in practice.”
She further shares that Gorilla Glue is in good shape in that regard — the company is already using available data combined with some good reporting — as it continues to build data literacy.
but this helps the business get familiar with the data they have and start to build the data
Regarding hiring talent in the data and analytics field, Tedesco says she has done a lot of recruiting. The key to knowing if you will like a career in data science is whether or not you liked the courses that led up to it. For example, is it just thinking critically about data and coding that you enjoy? If you don’t like coding, you probably won’t like data science, she advises. Bottom line: if you’re enjoying your classes, you’ll probably like being a data scientist. Her advice for young people or professionals is to take as many practical courses as possible. Learning tools like data mining courses or programming languages like Python, etc., are extremely valuable.
She advises finding an internship, even if it’s only partially relevant, and if not an internship, there are a lot of great competitions out there that provide relevant experience and understanding of what it’s like to work in data science. Her final words of advice? “Embrace your mistakes and learn from them because we all make them. There are great learning opportunities out there, even though they might be painful at the time.”
[This content was originally published on cdomagazine.tech.]
