Meet our Data Science students: “Math is less intimidating for me than art or history”

After graduating with a chemical engineering degree, I spent a couple of years teaching Physical Science at underserved high schools before joining Michelin. I started as a process optimization engineer and moved into management two years later. Having a solid engineering and management background brought me to the next opportunity at the Home Depot, the largest home improvement retailer in the United States. There I spent five years making processes and project management more efficient using Lean and Six Sigma tools.

When my family moved to Japan in early 2020, I struggled to find similar roles, as many of them understandably required knowing Japanese. I started looking around for skills that could help me make myself more marketable, and stumbled on Python. As my fascination for it grew, I decided to find a program to enhance my Python skills and learn how to use it in a work environment. This is how I found Le Wagon Data Science bootcamp!

First day of the Data Science bootcamp! Time flew so fast...

One of the things I really like is that most of the time is spent on actually doing, versus just watching a lecture. We learn a lot by practicing and solving challenges. All my batchmates are also deeply engaged and willing to help each other.

On top of that, I appreciate the patience of our amazing teachers. Obviously, they have a lot of experience in the field, but they are also able to break down their knowledge and explain it to us in a clear way. 

My favorite week of the course has been data engineering, where we learned how to turn our models and data analysis into products that others can use. 

Right now we’re going through project weeks, the most practical part of the bootcamp, where each team is working on a Data Science project. My team is developing a product for musicians, that splits songs into different stems. Users will be able to input a link to a song or music video and independently listen to vocals, piano, or other musical instruments. 

I have a strong calculus background and my work experience so far has been data-focused, so I already had a good grasp of statistical methods and statistical process control.

Some people say that math is intimidating, but for me, art or history is much more intimidating than math (laughs). With math, you can always validate your answer, or repeat methods over and over. That’s not really something you can do with humanities... 

Njeri made it to the finals at our alumni-only Codewars!

My dream job would be a product management role for a Machine Learning, Deep Learning or AI-focused company. I'm really enjoying the time spent on our project, and figuring out how to fit all pieces together. That also allows me to leverage on my background in people and project management. 

Community-wise, I intend to stay plugged in Le Wagon and keep learning to make sure my knowledge is up to date. I’m also working on a small project related to investments to keep my skills sharp.

I've worked in male-dominated fields in the US before and made sure I don't give people any reason to doubt my ability just because I’m a woman. It might feel intimidating at first, but as you grow as a professional, over time you will gain credibility.

There's a growing need for people who can process and communicate with data, and having those skills to process and communicate data to other people will be valuable no matter what you're doing. There are so many resources and programs available right now to learn on your own. Once you confirm that you really are interested, sign up for a course like bootcamp to benefit from the accountability of a community.

Thanks! Learning how to navigate the Japanese business world is the next challenge for me. It is even trickier than math! (laughing) 

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If you would like to hire or collaborate with Njeri, feel free to contact her via Linkedin!