Shontael Elward graduated from the department in 2020 with an MA. She currently works at Nationwide and has agreed to share some of what she’s been up to since graduation and to give advice to current students.
Tell us about your job. Where are you working, and what is your current job title?
I work at Nationwide (NW) within the Enterprise Analytics Office. I currently have three job titles / roles. I am a Consultant, Analytic Scientist – this is Nationwide’s internal title for a data scientist. I am also the Statistical Modeling, AI/ML ethicist. I am also the coordinator for the Undergraduate Opportunity Program; a program that recruits and hires OSU undergrads to work part time as Data Science Student Researchers.
How did you get your current job?
I got my current job because I was selected to participate in a program between OSU/NW. Nationwide has a relationship with OSU, that sits in the business school; together they created what is called the Nationwide Center for Advanced Customer Insights (NCACI, aka “The Center”). The Center recruits graduate students from across campus to work at NW as data scientists through a GRA placement. Nationwide provides full financial support to the students in exchange for 20 hours of work per week. While I worked as a GRA, NW offered me a full-time position which I accepted.
What do you do during a typical work week?
My typical work week now looks a little different than when I started so I’ll tell you about both. When I first started as a GRA and when I rolled over to become a full-time employee (FTE), most of my days were spent working on project work. Project work is whatever business problem you’ve been assigned and are supporting, so some kind of analytics / data science question. In addition to my project work I would also have some team meetings here or there and the occasional meeting with business partners to work on the project.
Now, my work has shifted quite a bit to some of the other responsibilities I mentioned above. I spend most of my time working on Data Ethics, work with The Center, other department duties like hiring, and meeting with business partners. I do still do some project work but it has become smaller and smaller.
Of the skills you acquired in graduate school, which skill is the most important or helpful for your job?
Critical thinking and quantitative analysis skills (stats, programming, data cleaning)
What do you enjoy about your job?
What I enjoy most about my job is that I have a safe environment to grow, learn and influence my corner of the world. The department I work in is what’s referred to as a centralized advanced analytics team. That means that there are about 130 of us, most with advanced degrees from varying backgrounds, working on the most advanced data science problems for the whole company. The culture of our department is very similar to a university. We are all life-long learners. Curiosity and the space to learn is encouraged and nourished and that is very important to me.
In my role as data ethicist, I am able to have real impact on the work of my department and company which in turn impacts all our customers and maybe eventually our industry.
In my role within “The Center” I support undergraduates. I really enjoy giving the students guidance and an opportunity to differentiate themselves among their peers with the work they do for us.
I care deeply about using my resources to improve the world and this job feels like an avenue to do that.
Do you have any advice for students who may be thinking about taking a similar career path?
If you want to get into data science or any kind of analytics:
- Get comfortable coding
- Learn stats
- Practice Exploratory Data Analysis & Feature Engineering
- Practice modeling (regression and beyond)
- If you can, do some predictive modeling
- Designing / collecting data is a strength you may have that is valued, but not really used very often. So make sure you develop some of the other analytic skills you need to solve problems AFTER you have data in hand.
- Figure out how to talk about the things you know with industry language
- Good languages to play with: Python, R, SQL
- It looks like lots of jobs are moving toward Python but R is still pretty strong and isn’t going away at NW
- In bigger shops (like NW) you likely won’t need to do your own data engineering or pull you own data often (SQL), but sometimes you will. I hear that in smaller businesses the SQL/data engineering is more important for a data scientist.
- Even if you’re not in comp ling, if you’re thinking about going into industry, it could be useful to learn some basics of NLP while you have classes/resources available to you - I wish I had.
Is there anything else you'd like to tell us?
I would like to say that I really love my job. I walked down this path of exploring data science in part because of the scarcity of academic jobs but mostly because I was worried about having to move my kids to a different city for a job. The academic market felt very unstable, even though I think I would have been an attractive candidate. I didn’t know if or where I could work, and if I did get a job would I be “stuck” there forever?! Many of my peers at Nationwide have left academia because they were unsatisfied with academia or burnt out – that was not true for me. My experiences in the OSU Linguistics Department were some of the most satisfying and supportive of my entire life. I truly love the people and opportunities I had there. Also, I really miss linguistics, even though I feel sure this is the right path for my life right now. I wish I could work on language problems or that anyone around me knew anything about linguistics; it’s a trade-off.
The other thing I’ll say is that the money is great. I did not make this move because of the money but now that I’m here I am grateful for the added security for myself and my family.
