Emily Kubicek | Data Strategy Manager
The Walt Disney Company
Los Angeles, California, U.S.
Department: Audience Modeling and Data Science
Education: B.A. Communication Sciences, San José State University, Ph.D. Cognitive Neuroscience, Gallaudet University
Career stage: Early
What do you do?
As a data strategy manager, I would categorize my job as 50% technical and 50% business. However, it’s important to note that the technical and business aspects are not mutually exclusive; much of my job involves mixing the two and deciding on the best decisions with both business and technical objectives in mind. Having been a data scientist on this same team prior to my current position, I leverage my technical understanding in ensuring external and internal clients work seamlessly with our data offerings.
What types of skills do you use?
Coding (SQL, bash, Python), data engineering, knowledge of various cloud services. How are applied mathematics and/or computational science important to what you do? The development of many of our data offerings is rooted in machine learning and other data-related concepts such as graph theory. Without a strong foundation in these areas, we would not be able to productize the insights and tools we have created using these advanced methods.
What are the pros and/or cons of your profession/job?
Pros: Work/life balance, liking the company I work for, and constant change.
Cons: I can easily see how working in tech can take over your life. It’s important to remember, even if you thoroughly enjoy your work, you should have a life outside of it.
Does your job offer flexibility?
Yes, I currently work both from home and in an office.
What career path did you take to your current position?
Ph.D. in Cognitive Neuroscience → Data Science Professional Intern → Data Scientist → Data Strategy Manager
Was your career path well planned or a result of taking opportunities as they arose?
Internships. Internships. Internships. In looking for internships be sure to cast a wide net—if in tech, look for a variety of roles, not just the one you think you want to end up with. A diversified toolset is always something hiring managers look for.
Was there anything that surprised you when you started out in your career?
You can still be technical and not model all day. I code, develop, and do amazing things with cloud services all day. All these things are as much a part of and needed in data science as modeling is.
My job would be categorized under the larger umbrella of technical product manager. Technical product managers handle small scale, large scale, one product, multiple products, etc., which makes the salary dependent on the responsibilities of that particular role. Scope of role is something I would keep in mind not only when researching jobs but also when negotiating salaries.
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