In the realm of data science, information is as powerful as it is unending. Likewise, more data is produced annually than ever before, and it’s predicted that will remain true in the future with each passing year.
In 2023, Statista projects the volume of data created, captured, copied or consumed will reach 120 zettabytes. Put into perspective, a single zettabyte is equal to a trillion gigabytes. By 2025, Statista projects this number to grow to 181 zettabytes — or 181 trillion gigabytes.
Data scientists find themselves amidst these almost unfathomable mountains of data, which grow every day. And in these vast expanses, a product and culmination of all aspects of humanity’s digital presence, data scientists become invaluable sources of information, investigation and insight.
According to the U.S. Bureau of Labor Statistics, the data science field is expected to grow by 36 percent between 2021 and 2031, a rate much faster than the average for all occupations.
Rather than being unprecedented, this predicted growth is — in a sense — inevitable. For organizations across every industry, data has become a guiding force and driver of profit.
As an increasing number of early-career data scientists forge ahead and seek opportunities, they can look to those like Motolani Alimi, an associate data scientist at Walgreens’ AI-lab.
Here’s what Alimi said about her day-to-day work, career track and what advice she has for her peers and up-and-comers.
Walgreens provides multi-channel access to consumer goods and cost-effective pharmacy, health and wellness services.
What is your data specialty and your current role at Walgreens? What does your day look like? What is exciting about it?
My career journey as an associate data scientist and part of the AI-Lab at Walgreens began from working as a full-time mom and a graduate student at Northwestern University, pursuing a masters in data science, as well as certifications in project management and a data science bootcamp. A year ago, I focused on AI and data engineering, and now, I am currently employed as an associate data scientist at Walgreens Boots Alliance.
Upon completing the first project, loss prevention, I became the project lead in pharmacy store performance analytics, which aims to re-imagine the pharmacy experience by leveraging predictive insights to uncover performance measurement that matters the most to Walgreens customers. I analyze the collective relationship among the pharmacy metrics selected and listed on the Walgreens Strategic Analytics Manager. The metrics include an operational scorecard, the core of pharmacy workflow, pharmacy of the future, Rx inventory metrics on the dashboard, and specialty data falling under operations. Additionally, Avaya phone metrics are examined to understand their correlation with the patient experience.
What influenced you to choose this career track in data?
In 2022, I took the leap of faith and applied to Walgreens as an associate data scientist, with an undergraduate degree in psychology and after completing my masters at Northwestern.
I find inspiration in my faith, my family and my awesome, multi-talented team members at WBA, who blazed their own trail in the AI and data science world. Throughout my professional journey, I have cherished the opportunity to collaborate with remarkable team members; facing different projects with openness, a willingness to learn and fostering valuable connections I encounter daily have helped to transform my career and reputation at Walgreens.
I find inspiration in my faith, my family and my awesome, multi-talented team members at WBA, who blazed their own trail in the AI and data science world.”
What advice would you give to someone considering the different career tracks? What should they consider in their decisions?
Embarking on an early career professional journey towards a data science career might appear daunting, but aspiring data scientists have multiple avenues to enhance their knowledge and gain practical experience. The presence of numerous mentos has been instrumental in my personal growth, fostering valuable connections throughout the process.
