Effective Communication, the (Racing) Heart of Data Science
Heaviness. Difficulty focusing. Uneasiness. A racing heart.
Why am I describing symptoms of anxiety? Because at the moment of writing, I am experiencing all of them.
Beginning a blog dedicated to my journey in learning data science doesn’t evoke this feeling per se. Actually, I look forward to sharing my work with the community. I’m excited, anxiety’s twin emotion, for this endeavor.
Writing the actual posts, especially this first one, is where the excitement turns to anxiety.
This is ironic because I believe effective communication is crucial to success in data science. For today’s inaugural post I will share where I’ve been, where I’m going, and how I plan to learn to communicate in the midst of writing anxiety.
Where I’ve Been
Most recently I’ve been a manufacturing engineer in the automotive industry. I helped test automotive lighting units for compliance with national government regulations, industry standards, and company quality assurance. This work generated photometric data as a primary evaluation metric. In handling this data stored in dozens of Excel spreadsheets and CSV files, I attempted to automate analyses and visualizations using VBA 😬. My data science toolkit was in its infancy.
Concurrently with this role, I discovered (thanks Google!) and became enamored with two things which set me on this data science trajectory.
- Brit Cruise’s YouTube channel (Art of the Problem), which tells the history and explains the high-level concepts of cryptography, information theory, computer science, and (not at the time, but fitting nonetheless) deep learning.
- The world of Python programming.
Having completed a chemical engineering degree at The Ohio State University, I had some exposure to coding. A favorite course of mine was Dr. Rathman’s “Modeling and Simulation,” where we applied chemical and biomolecular principles to model processes and perform simulations in MATLAB. However, I did not have much exposure to computer science concepts or to open-source software such as Python. I began teaching myself some basic Python and kept diving into Art of the Problem’s content. Also, this “data science” phrase kept coming up in my YouTube recommendations (the irony)!
As I learned more about all these topics, I came to realize that proficiency in data science is where I wanted to take my career. I enjoyed a similar type of work in college. I enjoyed this work even with subpar tools in my automotive engineering job. I enjoyed learning the discipline on my own time.
I decided to volunteer and attend a data science conference to continue my learning, and then I started and completed a professional education course through Ohio State for a Certificate in the Practice of Data Analytics.
Where I’m Going
Currently, I am participating in Flatiron School’s data science program, where I’m excited to continue my transition into a data science role. I am looking forward to learning new tools and techniques, such as Git and version control, web scraping, cloud computing, and a host of advanced machine learning algorithms. Most of all, I am eager to add to my portfolio of data science projects and share my journey here.
One way I visualize success in my career is by analogy to a vector quantity, like velocity, which has both a magnitude and a direction. Both matter. The magnitude is akin to my effort and the fit I have in my chosen career path. I believe data science is a good match here. The direction element is where I’m having an impact. The problems I’ll be helping solve using the tools of data science are an important part of achieving personal success for me.
Healthcare, climate change and energy, and biotech are a few of the industries where I have an interest. Above all, I want to solve interesting problems with good people. If I’m fortunate enough to do that, that’ll be success.
Communication Plan
One of my goals in writing this blog is to improve both my writing efficiency and effectiveness in the midst of anxious feelings and thoughts.
By efficiency, I mean the time and effort it takes me to transfer the ideas in my head to the written word.
By effectiveness, I mean the clarity and conciseness of my writing. This is closely tied to the value it creates for you, the reader, and myself, the writer. The more clear and concise my writing is, the easier the transmission to you and the better structured my thinking becomes.
To achieve this goal, I plan to follow two principles.
- “Work with the garage door up.” I plan to honestly document how my progress is going in regards to this writing goal. I will communicate what has been a challenge as well as what is going well.
- Test different writing techniques against reality to create a process that works for me. I will read about and test different writing techniques to find what works well. There is a lot of advice about how to write. I’ll try a lot and communicate what I’ve found to work.
In regards to working with the garage door up:
- Efficiency: It’s taken me more hours to write this than it’ll take you minutes to read. I’d like to monitor this ratio (currently ~1.2). It also took me two days to begin writing once I intended to write.
- Effectiveness: This will be measured by any reader feedback.
In regards to testing writing techniques:
- I tried writing the big ideas of my post in a bulleted list. Then, I ordered them. I added more detail in sub-bullets to a couple of the big ideas, but not all of them. Finally, I composed the writing. This chunking method worked well for the big ideas, but I felt like I needed to start writing for the details to come. I’ll try this again and see how it goes.
- I wrote the big ideas at the start of the writing period. I’m going to try to do this earlier in the process, days or weeks in advance rather than an hour.
- Closely related to above, I wrote in one long writing period rather than a few or many smaller ones. I’d like to try shorter writing sessions.
Thanks for reading about my path to data science so far and where I plan to go next. I hope my honest and structured approach to improving my writing is valuable to you, whether as a fellow writer or an interested reader.
