Data-Birds is proud to present April’s Data-Bird of the Month:
Svetlana is an accomplished software engineer and data scientist, and is now a Principal Algorithms and Machine Learning Scientist at Walgreens Boots Alliance.
Coming from a family of engineers and mathematicians, Svetlana continues the family lineage of technical professionals, raising two daughters pursing technical careers (future data-birds!), one having studied at Illinois Institute of Technology, the other recently accepted into MIT.
All words after the stated question are Svetlana’s. We’re so excited for you to hear her story and learn about the journey of another seasoned Data-Bird.
We’re two months down in 2021 which means it’s time to meet our second Data-Bird:
Alexandra is a Senior Associate Data Scientist at a financial services company MSCI. Much of her work is dedicated towards automating anomaly detection tasks and text classification problems.
She is an intelligent and curious data professional, mother and competitive runner! Alexandra continues to push her areas of expertise and writes semi-regularly for the Towards Data Science publication (see her articles here).
All words after the stated question are Alexandra’s. …
We, at Data-Birds, are THRILLED to announce our very first Data-Bird: Dr. Kathleen Perez-Lopez. As our January Data-Bird, we take a deep-dive into Kathleen’s life and career in tech.
Kathleen shares her experience navigating the tech industry of the 70s/80s/90s/00s/10s, raising a family while nurturing her fierce curiosity for math and technology to achieve high social impact.
All words after the stated question are Kathleen’s. It was an honour to ask these questions and gain insight into Kathleen’s diverse and impressive career and we’re so excited for you to hear her story.
Without further ado…
I am either in-between positions…
Data-Birds is a space founded with the sole aim of amplifying women’s voices in data. Follow along as we get a data-birds-eye-view of the women infiltrating the industry of the future.
Each month, we aim to feature women and fem-identifying data professionals as our ‘Data-Bird of the Month’. We hope to learn more about women’s stories navigating this industry and highlighting their career achievements. We hope this space provides inspiration for other women aspiring to become leading data professionals themselves and women already in this field.
This publication will feature interview-style articles with our Data-Birds. …
This is Part III of a three-part series on interview prep for software engineers.
The plan is designed to implement the deliberate practice approach which I wrote about in Part II.
Use this as a guide — the main aim here is to follow the principles of deliberate practice and the 7-step flow I will talk about below. Enjoy the ride!
Ok, we’ve had a big discussion about what deliberate practice is but let’s now talk about how…
In Part I of this blog series, I discussed the idea of treating onsite technical interviews as auditions rather than interviews and that we can utilise practice techniques adopted by professional musicians to ensure our preparation is more efficient and geared towards success.
One such practice technique is a method called deliberate practice which I will deep dive in this blog. Be sure to check out Part III that outlines a study plan implementing deliberate practice.
In Part I, I touched on the idea of deliberate practice¹, a term coined by Dr Anders Ericsson and identified as a method used…
This is a three-part blog series which I wish to have a discussion on how we approach technical interviews.
In Part I, I’ll touch on why I think this is necessary and relevant.
In Part II, I speak more specifically about the concept of deliberate practice and how to think about it in context of the technical interview.
Finally, in Part III, I get really specific and actually build a study plan for software engineers preparing for their interviews! I also give some notes about data science interviews!
If you’re reading this, then you’re most likely going through the grind…
If you’re living in the US, you’ve likely been under some form of ‘stay at home’ order for 5 months now (coming into 6 months!). This is longer than any other country in the world has been in isolation for.
Why did we go into lockdown?
To slow the spread right?
Well… yes… but the main reason for us all to go into isolation, was actually to buy the government time to put together a plan of attack to address the many, many flow-on effects (health, social, economic etc.) that a global pandemic initiates.
This time period wasn’t just about…
As the subtitle suggests, this code-along post is for beginners interested in making their first, more advanced, supervised machine learning model. Perhaps you’re wanting to know how to improve your Titanic score on Kaggle — well this code along will show you a way that could boost your score significantly straight away.
This is for people who learn best by doing.
My aim is to demystify the application of machine learning. Yes, the theory behind machine learning can be quite complex and I strongly encourage you to dive deeper and expose yourself to the underlying ‘math’ of the things you…
We all know that there is a huge demand for qualified data scientists in the industry. So how are we exposing the world of data science to students?
I think it’s important for students to be aware of industry standard tools from the beginning to help shape the way they learn and think about problems.
With this in mind, I want to think about how students can get started with learning about these tools without having the hands-on machine learning experience that is often assumed knowledge when coming across these tools for the first time.
So, I wanted to write…