|From:||San Francisco, USA|
|Course:||Foundations of Data Science|
|Before Springboard:||Enterprise Architect, Marketo|
Without Springboard, there's no way I would be where I am today: doing what I'm passionate about at a company that I'm honored to be a part of.
If someone had told me that I’d be working for Pandora as a finance data analyst upon completion of the Foundations of Data Science course, I probably would have laughed it off. And if they had added that I’d be working for my Springboard mentor, I definitely would have laughed it off-- too good to be true! But that’s how things played out! I no longer pinch myself when I walk into the office, but I happily face each day with hard work, gratitude, and an open mind-- just like I approached the Springboard course.
I signed up for Springboard because I was hoping to transition from engineering to data science. Engineering was fun, but much of the demand today is for apps, which don’t really excite me. I find it much more interesting to use that same engineering skillset to weigh in on business problems with far-reaching implications, like predicting downturns and upturns for a company, rather than solving technical challenges. It’s more prevalent than ever that data drives decision-making, and data science is the art of coming to those strategic decisions.
By the end of the course, I was able to really improve the performance of the models that I had built into my project.
I had tried various online learning sites such as Lynda, Udacity, Khan Academy, and Code School. They all were extremely effective as starting points, and many of them are featured on Springboard. The difference between these and Springboard is that they all provide courses on specific topics, whereas Springboard provides a structured curriculum to go from point A to point B. In the case of my data science curriculum, Springboard was able to take the field of data science, identify the key skills needed (both theoretical and practical), structure an intuitive learning path to acquire each skill, and challenge me with a final project that makes use of all of them. Without that careful curation of content, I wouldn't have been able to figure out what I needed to learn in the first place.
Initially, I was unsure whether I would have the amount of time necessary to devote to the program. However, the self-paced nature of the program combined with the patience of my mentor made this a non-issue, and I was able to complete the course without any pressure of a deadline.
I am a very self-motivated learner, but Dave was extremely helpful in pointing me in the right direction for research. I was able to take the skills that I learned from Dave into my previous job role to solve challenges in ways that the management team hadn’t thought of.
Though a lot of the initial coding and statistics modules in the curriculum came pretty easily to me, I struggled a bit to apply all of the things I was learning when I got to my capstone project. I love to cook, so I set out to identify overlap in regional cuisine to understand how different cultures may have been influenced. Dave was patient and helpful in making things click-- by the end of the course, I was able to really improve the performance of the models that I had built into my project.
I often joke with my friends that my job is to use math to predict the future. It's a funny way of putting it, but that's really what I get to do every day. Most of my work involves forecasting various usage metrics, such as hours of music streamed and active users. It's very important that these forecasts be extremely accurate since they affect several lines of business throughout the company.
The number of things I have to learn every single day is staggering, but it’s a good type of challenge. We have access to most data points the company has, so there’s a lot of freedom to do ad-hoc analyses and hackathon projects. The culture here encourages you to grab some data and answer some questions. I love it when I’m in a team meeting, ask a question, and everyone shrugs and says, “Good question-- we aren’t sure, but I bet we could use the <something> data to figure it out.”
I anticipated a long, difficult path to the data science field, but Springboard helped me accelerate that. I’m so grateful that Dave reached out to me within a few months of my Springboard graduation in order to jumpstart my Pandora interview process. Without Springboard, there's no way I would be where I am today: doing what I'm passionate about at a company that I'm honored to be a part of.
I’m grateful that Springboard was the beginning of my data science journey.
Before : Business Analyst
After : Data Analytics and Data Pipeline Consultant
"I left academia almost two years ago, and I have no regrets."
Before : Instructor, MIT
After : Data Scientist, Wayfair
Springboard is a wonderful stepping stone to get to your goals in Data Science.
Before : Research Officer, British Columbia Government
After : Data Scientist, Boeing