Lead Data Scientist Says Her Job Is Never Boring!

Name: Maia Frieser (she/her)

PhD: Behavioral Genetics, University of Colorado - Boulder, 2020

What was your main area of research?

I studied the relationship between adolescent cannabis use and later educational attainment. I compared the educational, financial, and family-formation outcomes of those who had been heavy cannabis users in adolescence but ceased in adulthood to those who had never used cannabis heavily, and those who began heavy use as teenagers and continued using into adulthood. I also studied a high-risk population who were in juvenile detention or jail as adolescents to see if similar patterns of later-life success held.

I used an identical twin sample to begin understanding causal relationships between cannabis use and education.

What is your current job?

I am a Lead Data Scientist at Lumen Technologies Inc. in Arvada, Colorado (Denver area).

I lead a data science team at a telecommunications company in our Product organization. I am responsible for leading multiple large-scale projects utilizing real-time network health and telemetrics. I also work with vendor teams to review code, manage production deployments and enhancements, and to provide guidance around our in-house predictive models.

What is your favorite thing about your job?

I love getting to explore large data for predictive insights. It's a great mix of experimentation and application, and I have to move quickly. It's never boring!

What is the most important skill you developed or experience you had during your PhD that now helps you in your current position?

Explaining technical or niche concepts to those without a similar experience is something I do every day.

How did you build the skills necessary for your current role?

I took courses in R and statistics which I use daily.

Teaching was also particularly helpful because it helped me learn to communicate clearly and effectively with people who don't have the same areas of expertise or understanding.

How did you find this position? What were the career steps you took to get to where you are now?

PhD graduate ➡️ HR analyst (large healthcare company) ➡️ Senior HR analyst (large healthcare company) ➡️ Data Scientist (small healthcare startup) ➡️ Lead Data Scientist (Current)

If someone is interested in a similar role, what would you recommend they start doing now to prepare?

Brush up on LLMs and practice working with AI/ML in a cloud computing (GCP, Azure, AWS) environment. Understand the practical and ethical implications of AI, and be able to comfortably explain stats or AI/ML concepts to those with no background in it.

Why did you decide to not pursue a career in academia?

It came easily. I saw the struggles for funding and the location-bound nature of academia and realized that I don't necessarily need to be the person asking the question, but I'm happy to be the person answering it.

I wanted the unique combination of structure and freedom that an industry role has given me, with prescribed hours, work/life balance, and the ability to be located wherever works best for myself and my family.

I wanted the flexibility to work quickly on multiple projects instead of focusing on one area long-term.

What advice do you have for someone getting their PhD and looking to pursue a career outside of academia?

If you have no previous corporate experience, even with a PhD, you will be an "inexperienced hire". Companies may be more wary of offering very high level roles off the bat to an inexperienced new graduate. Be willing to work your way up and know that the titles in data science/analytics are very flexible, and the role description may be very different from the title.

And don't hesitate to reach out and network!

Are there any components of your identity you would like to share, including how they have impacted your journey?

This isn't about identity, but I was my department's first ever Zoom defense during Covid lockdown (3/31/2020). Everywhere I had interviewed was in a hiring freeze, and I took what I could get in terms of a job, which is why I ended up in a more entry level role at the beginning of my post-PhD career. In a different world my experience may have been much different!