Sheldon Smickley is the CEO and Founder of Podible, a podcast discovery platform. After a stint in marketing agencies and solutions engineering, Sheldon actually built the prototype for Podible while attending Springboard’s Online Intermediate Data Science: Python Course! Learn why Sheldon strongly believes in the Springboard mentorship model, see the data science tools he learned throughout the course, and why technical skills have made him a better leader.
What is your pre-course story? How did your background in analytics and solutions engineering lead you to founding a company?
I studied Economics as an undergrad at Rutgers, but I focused pretty heavily on the quant side. I saw a lot of potential in the marketing and advertising space so I worked in analytics for about four years in the agency world. Building my company, Podible, really started during my Springboard capstone project.
Did you go to Springboard knowing that you wanted to start a company?
Nope, I went to Springboard because I wanted to become a data scientist at a high-skill tech company or to become a data engineer. The idea for Podible came about because I’m a pretty big podcast fan, but I couldn’t find new podcasts based on the podcasts I searched for and listened to. There’s also a podcast boom right now and the ecosystem is kind of crazy.
What motivated you to enroll in a data science course?
I really wanted to dive into machine learning and pursue a data science role with heavy analytics. When I was working at an agency, I was writing a lot of scripts. For instance, one of my former agency clients was a large finance company and we did a long report for them that took an analyst three weeks to complete. By writing some scripts in Python and R, I was able to get that report done in three minutes, and we were able to use that time diving into the data and coming up with more useful insights.
That inspired me to how I could use Python to dive even deeper into the data. I saw that it was crucial to have a background in Python and machine learning to get a heavy analytical role at Facebook or WeWork.
Springboard actually wasn't the first coding course that I did. Before I pursued data science, I did Bloc’s Rails bootcamp for software engineering.
While researching data science courses, what stood out to you about Springboard?
I was the total opposite of the Springboard student – that Ph.D. student who wants to switch careers out of academia. Instead, I was the hacker and the doer who tried to figure things out by reading documentation and learning on my own. I looked at courses on Udemy about how to use Python in Pandas, Spark, and their documentation on Python in data science. Those were $10-$15 courses. Then I tried the Coursera data science program, but I actually dropped the class because I found the support was pretty low.
What I wanted - and got - from Springboard was mentorship. I completely believe in the mentorship model – there are definitely individuals who are self-motivated and want to learn on their own but adding a mentor as a resource enables them to get through the learning process.
I also liked the fact that Springboard tested your knowledge in order to be accepted. The application required writing a simple Python loop, writing a little bit of code, and an analytics test. I liked that they curated the candidates that they accepted.
Was it important for you to learn online?
The online aspect was pretty big for me. I actually tried an in-person, expensive coding bootcamp in New York, but it didn't give me the resources that I really wanted. It felt like we were going through a canned curriculum versus being able to go off track and really think – that's how you discover and actually grow versus just learning a lesson. I didn’t finish that bootcamp program because it wasn’t working for me.
At Springboard, the mentorship aspect combined with the online aspect meant I could take the course at the pace I wanted. I also really liked the capstone project because I could work on my own idea which was really exciting to me.
Tell us about your Springboard cohort – were your classmates’ backgrounds diverse and did you get to learn with other students?
It felt very diverse in regard to different ethnicities and genders, and there were people from a lot of nationalities. It felt like most of the other people in my cohort were academia-focused. There were about 25 people in my cohort, but most of my interactions were with Tony, my Springboard mentor. Most of my learning was done with Tony, but I did love the idea of having a dedicated Slack channel and being able to reach out to people if I had questions.
You already knew some Python before Springboard, so could you walk us through what you actually learned at Springboard? Was there a curriculum that you followed?
I previously knew web development with Python, using things like Django & Flask, but I had little experience using scikit-learn and the pandas libraries.
I was impressed with the curriculum they offered. It started with solidifying the basics of statistics and ended with using advanced machine-learning libraries that could be applied in your day-to-day as either an entrepreneur, analyst or data scientist. My favorite part of the curriculum outside of the capstone project was going through the machine-learning section from Harvard’s Data Science 101 course and doing the homework in Jupyter Notebooks.
Okay, tell us about your final project at Springboard, which would become your company today!
I was working with Tony, who was amazing at helping me throughout the entire course. He was really supportive and I could bounce ideas of off him and see if my ideas actually had legs.
I created a podcast search engine during the last month of Springboard’s Data Science course. It was a very basic Flask Python app where I transcribed a podcast from audio to text and then we took those podcast transcriptions, sorted them into specific models like topic model libraries. I searched those libraries and was able to actually see related episodes based on the content that was being discussed in the podcast. Until then, I only found really basic apps that searched the title or description.
What tools did you learn and use at Springboard to create Podible?
During Springboard, the app was actually called Podly, and the tools were very basic. I used Python with a Flask back-end and I used the Gensim library for topic modeling (topic modeling is when you automatically identify topics in text and use that to find hidden patterns). For the transcription side of it, I used a pretty well-known audio-text based transcription project called CMU Sphinx (Carnegie Mellon University Sphinx). Once you compile it you can actually write an audio app in that tool.
Today, the tools we use for Podible have completely changed. We’re now using a Django backend with React / Redux frontend, and for data engineering, we use Spark and Scala. It’s one thing to build a prototype with a few podcasts, but if you’re going to build an application that supports thousands of users simultaneously and transcribing hundreds of thousands of Podcasts, you need to up your tools and bring on experts to your team.
How long did it take you to complete Springboard?
I was working full-time at the time, so it took me the full three months to complete the data science course with Springboard, from the first lesson to the completion of my capstone.
Did you feel like your mentor, Tony, was able to support your entrepreneurial goals?
I felt really supported by my mentor. He had connections at Uber, gave me feedback on my project, and even introduced me to some VC’s that I could bounce ideas off of. I was still testing the waters at that time so I wasn’t truly sure about Podible. It was probably about four or five months after Springboard when I thought, "All right, let's really go all in and pull together a team.”
As the CEO of Podible, how do you spend most of your time? Walk us through your day-to-day and tell us about your team.
We have a full-time team of four people and one part-time person, and we’ve raised some money and now work out of a WeWork.
In regards to my day, 40% of my time is spent on coding, reviewing code, and helping build out the app with my CTO and our other software engineer. Our CTO is much more technical then I am – he went to UOC Berkeley and studied electrical engineering, computer science, and mathematics. He has a stronger traditional background – I completely agree with the theory of hiring people that are better than you.
30% of my time is spent in meetings with VCs, fundraising, and speaking to customers with our Chief Advisor who works in the VC space. He's helping us move in the correct direction because it’s a really competitive landscape and we want to make sure that our unique strategy works.
And the remaining 30% is spent on the marketing and analytics side, working with my Marketing and User Acquisition guy and helping grow our user base.
What skills from Springboard made you a better CEO and founder?
I think the most important skill was learning how to learn. I definitely learned that at Bloc but it was reinforced again at Springboard. When I don't know how to do something, I go and research it heavily, read about the documentation, read what other people are doing, and keep on coding to learn even more.
What's been your biggest challenge to learning data science or applying that to Podible?
I think the biggest thing is reading too much and not getting started right away. I think that's the biggest piece of advice I can give to someone asking for a big take away from this process. People are so focused on heavily preparing for a goal, that they don't ever get started. Whether you're going to go build your company or you're going to go learn data science or how to code – stop researching and actually go and get started. Even if you fail, that's absolutely fine.
I've had a million ideas and this is the first one that I pursued heavily to the point where I quit my full-time job. I have employees who have quit their jobs and are banking on this to work out; that pressure is the best learning experience.
What advice do you have for aspiring entrepreneurs or entrepreneurs who are already working on their business? Do you suggest attending a coding bootcamp?
If you are going to build an app or a product in the tech space, then you need to have some technical understanding. If I take my car to the shop, and I don't have an understanding of how the car actually works, then the mechanic can do whatever he wants. If he wanted, he could cause more harm than good, or give me an outrageous price for something relatively simple.
Alternatively, you could hire someone who you trust a lot as your CTO. My CTO is a former direct report when I was a Solutions Engineer. We have a really good friendship and a good understanding so I trust him with my life. But without any kind of technical background, I wouldn't be able to help build out the app. I don't think someone can just come up with an idea, not have a technical background and then outsource the entire project. That won’t work out well.
Having technical skills is the most invaluable advantage you could have in our current day and age – understanding how code and technology works. I’m not the CEO because I came up with an idea; it’s because I have a vision but can also provide value back to the team at Podible.
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Lauren is a communications and operations strategist who loves to help others find their idea of success. She is passionate about techonology education, career development, startups, and the arts. Her background includes career/youth development, public affairs, and philanthropy. She is from Richmond, VA and now currently resides in Los Angeles, CA.
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