Data Science Career Track
Mikiko Bazeley
Before Springboard:
Data Scientist at Autodesk
After Springboard:
ML Engineer at MailChimp
My mentor would give valuable feedback not just on my capstone projects, but also on how to interface with key stakeholders, how to use model interpretability tools like SHAP and LIME. At times, they even served as that positive counterbalance to my constant feelings of impostor syndrome.
My mentor would give valuable feedback not just on my capstone projects, but also on how to interface with key stakeholders, how to use model interpretability tools like SHAP and LIME. At times, they even served as that positive counterbalance to my constant feelings of impostor syndrome.
Meet Mikiko Bazeley, a graduate of Springboard's Data Science Career Track.

Here at Springboard, not only do we pride ourselves on our students’ successes, but we genuinely believe that their dreams are what make up the foundation of our mission. Our alumni dream big – and they make big moves in stride. So, in our series of Student Spotlights, we’re shining a light onto some of our favorite alumni stories: their journeys tell stories of accomplishment, grit, and determination against all kinds of odds.

In this post, we introduce Mikiko Bazeley: hair salon receptionist turned Springboard Data Science Career Track alum turned Data Analytics Career Track mentor. Read all about her journey below.

A little bit about Mikiko…

Mikiko graduated from UC San Diego in 2013 with a B.A. in Economics & Anthropology. She joined the Springboard Data Science Career Track in October of 2018. After 6 months, she completed the curriculum and began the job search phase of the course. 4 months later, she landed a role as a Data Scientist at Livongo, one of the leading digital health companies empowering people with chronic conditions to live their best lives.

What initially interested you in data science?

When I graduated from UC San Diego in 2013 with a B.A. in Economics/Anthropology, I struggled for a few years trying to find my dream career. My first job post-graduation (and the only one I could get at the time) was working as the front desk girl at a hair salon.

I had a strong desire to go into the tech industry and work for a startup –like many of our clients were doing. After spending a while what felt like watching from the sidelines, I quit the salon and landed my first role as a growth hacker for an early stage recruitment tech startup. At that point, the motivation was in knowing that I wanted to go more into data and the determination to learn more about the industry and the different kinds of roles it offered.

I’d spend my days working and my nights and weekends taking online classes in programming, math, and database development. Iteratively learning more about this emerging discipline called “data science” and understanding that I needed some structured foundations, I applied to – and got! – a hybrid data analyst/data scientist role at Autodesk. I was thrilled!

But then, I promptly began to run into challenges as the very junior “data scientist on an island”, some of which included accessing, processing and visualizing big data for machine learning. I realized I didn’t have the tools, specific skillset, or resources to learn and develop into the kind of data scientist I wanted to be.

Eventually, I had the chance to interview for an internal data scientist role on a different team – and completely bombed the interview. During the post-interview debrief I asked the senior data scientist what I could have done better: she encouraged me to try to find a place where I could work on data science projects to get more hands-on experience.

What was your Springboard experience like?

When I chose Springboard I was focused on finding a program that had a few key factors:

(1) Cost

(2) Ability to continue working full-time

(3) Program flexibility

(4) Mentorship

(5) Project portfolio building

From there, I found my Springboard experience to go above and beyond those qualifications: the program was incredibly helpful and impactful in my job search for a data scientist role. The curriculum is fantastic, the mentorship amazing, and the structure allowed me to continue working and maintain my financial liquidity.

As part of my capstones, I focused mainly on using the tools and skills I learned in the curriculum to initiate and execute data science projects at my current company to get the real-time, hands-on, apprenticeship-like experience.

What was your relationship with your mentor like?

My mentor would give valuable feedback not just on my capstone projects, but also on how to interface with key stakeholders, how to use model interpretability tools like SHAP and LIME. At times, they even served as that positive counterbalance to my constant feelings of impostor syndrome.

I’m so grateful to have had the opportunity to learn from such an experienced data scientist and am thankful to count him as part of my professional network.

What was your capstone project?

Predicting Outcomes of Demo Calls for a SaaS Sales Oriented Company :) For this capstone, I implemented the first predictive model for my sales organization, utilizing XGBoost to classify qualification of sales demo calls in order to improve pipeline forecasting efforts.

The capstone is a demonstration of the value that seemingly low-hanging fruit data science projects can have on business organizations like revenue operations and the kind of collaboration that can happen between data scientists and business partners.

What was the most valuable part of your Springboard experience?

Hands down, the most valuable part of the Springboard experience was the mentorship and portfolio projects. I learned so much about data science and I felt supported whenever I ran into technical questions or parts of the projects that my team at work couldn’t help me on.

As a Springboard Mentor, what advice do you have for those considering online learning?

Commit. Sometimes I feel that my students don’t take online learning seriously because there isn’t a prestigious degree or certificate attached. The reality is that online learning is about the skills and experiences you personally develop and how you later use them to solve problems. It’s crucial to understand how the skills and the ability to learn are the most important tools in your professional career.

Courageously say “YES!” to YOU. By not giving ourselves permission to pursue happiness and genuine fulfillment, we are wasting a resource that so many wish they could have. YOU have every right to be happy, to experience a fulfilling career, to make a global impact. You just have to say “Yes”.

Ready to start or grow your data science career? Check out our Data Science Career Track —you’ll learn the skills and get the personalized guidance you need to land the job you want.

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