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Yelyzaveta Losieva: Data Scientist, Machine Learning Engineer, Deep Learning Engineer, NLP Engineer

I strongly believe you can solve and achieve everything if you love, what do you do.

Yelyzaveta Losieva LinkedIn: @yelyzaveta-losieva
Data Scientist, Machine Learning Engineer, Deep Learning Engineer, NLP Engineer
🎤 Hi, сould you introduce yourself?

Hello everyone! My name is Yelyzaveta Losieva and I'm Data Scientist, Natural Language Processing Engineer, Open Source Contributor, and Arctic Code Vault Contributor by GitHub (read more about GitHub Archive Program🔗). I was born and currently living in Kyiv, Ukraine. I'm passionate about problem-solving in data science, especially in the natural language processing field. Also, I actively support women in STEM and love to give public talks to encourage and inspire women and technical talks about data science. I was a member and one of the leads in Women Techmakers and Women Who Code Kyiv. I was a Grace Hopper Scholar 2016 Houston, Texas, and had won the Women Who Code Travel Stipend to Google I/O in Mountain View, California in 2017 and Google Travel and Conference Grants to attend the ACM Celebration of Women in Computing womENcourage 2018 in Belgrade.
I strongly believe you can solve and achieve everything if you love, what do you do.

🎤 What are you working on?

Currently, I continue doing my self-education in Data Science and at the same time, I'm doing different Open Source projects in Github. One of my goals is to continue creating and contributing to different Open Source GitHub repositories in Data Science (github.com/ElizaLo/Data-Science 🔗), Machine Learning (github.com/ElizaLo/Machine -Learning 🔗), Natural Language Processing (github.com/ElizaLo/NLP-Natural-Language-Processing 🔗), Interview Preparation for FAANG (github.com/ElizaLo/Interview-Preparation 🔗) etc., which includes not only awesome lists at this topics, but also some theoretical information and best practices and optimal implementation on Python.
Also, one of my goals is to create a blog where I will explain easily from scratch to explain complex topics from the data science field.

🎤 What work experience do you have?

During taking my Masters's degree in Computer Science I was working in Luxembourg startup Unicorn Nest as Supervisor of researchers. Since we didn't have any dataset then my goal was to collect and create it. I was coordinating the work of all existing junior researchers/data operators in creating a dataset for training the neural network. Monitoring the results of their work and the results of NER (Named Entity Recognition) and fact extraction from articles written by different people on various platforms by an existing neural network.
This work gave me experience and a deep understanding of creating complex deep learning neural models from scratch when you don't have anything, even a relevant dataset.

🎤 How did you get into your field?

To begin with, from early childhood I was interested and excited in the technology field. I mean that I’ve always been interested in such type of questions: «How this machine or mechanism works?» and «Why does it work that way?».
So in middle school, I became really interested in physics and IT and in recent years I was interested in programming. For example, in high school, I have learned HTML. So in eight grade I already strongly decided that I will connect my life with programming. Also during the last four years at school, I’ve taken part in the physics and web-design Olympiad. Among the school subjects, I liked mathematics, physics, and programming the most.
Then I enrolled at the Taras Shevchenko National University of Kyiv at Faculty of Computer Science and Cybernetics with a scholarship program and got a Bachelor's degree in Applied Mathematics. That gave me great knowledge of various mathematical disciplines. After that, I decided to get a Masters's Degree in Informatics. During studying Masters I got excited about Data Science and especially Natural Language Processing.
During my studies at the university, I met a lot of amazing groupmates that continue inspiring me even nowadays. Also, I was very active and tried to attend as many different professional meetings as possible and to communicate with different people at them. Later, many of these people became my friends and also influenced me to get into the tech field and chose my own way.

🎤 What stack of knowledge is needed to become a good professional in your field?

Since I am interested in data science, I can say about it:

  • Good math knowledge is definitely needed (especially algebra, calculus, statistics and theory of probability).
  • Knowledge of Python or R (depends on what you want to do), SQL a plus.
  • Knowledge of common ML frameworks.
  • Great knowledge of machine learning algorithms and deep learning.
  • Research and experiment with state-of-the-art machine learning/AI algorithms to solve critical business problems.
  • Ability to read, understand, implement and apply to business project recent research papers.
  • Proficiency with at least one of the Cloud providers.
  • Ability to write research papers in future.
  • Easily explain complicated things from scratch.
  • Give public talks at conferences and meetups.
  • Will be a great plus to know natural language processing or computer vision or both.
  • Creative and entrepreneurial mindset.
  • Passionate about AI.
  • And of course good soft-skills, strong verbal and written communication skills.
🎤 Describe your first project and what is your role in it.

One of my biggest solo projects was my Master's thesis. I was doing Question Answering System based on SQuAD v2.0 Dataset: comparing BERT and BiDAF models. I analysed two versions of SQuAD dataset (v1.1 and v2.0) and had chosen the last one which exists unanswered questions or questions with no answer to create QA system which takes into account the context of the sentence.
I implemented two models which include attention mechanism, namely BiDAF model (from the scratch) using GLoVe word embeddings and BERT-small (using Hugging Face library). I trained it on CPU and used EM (exact match) and F1-metrics to compare and analyse results.

Also, in another project I created a method to detect edges of cells using convex optimization, namely the Alternating Direction Method of Multipliers (ADMM) from a single image of the cell made by microscope to help earlier diagnose Cancer.
This was implemented in C ++, without using any additional libraries.
I tested this method on a large number of photos of cells made under a microscope and made sure that the proposed method works and it can be used in medicine.

🎤 What difficulties did you encounter along the way?

At first, I sometimes did not believe in myself and my strength, but then I realized that I can deal with everything and everything depends on me. Also, I have always had great support from people that surrounds me.
Also, one of the key roles was played by the fact that at that time I won several scholarships. The main was a scholarship that effort me to visit Grace Hopper Celebration 2016 in Houston, Texas. This conference inspired me the most and helped me to believe in myself.
After came back to Ukraine I became and still are a member of different communities, which support and inspire women in tech, such as Women Who Code Kyiv and WomenTechmakers.

🎤 I know you have won several scholarships during your studies in university and have visited a lot of conferences all around the word including tech conferences and conferences of inspiring women in STEM. Can you tell a little bit more about this: how to apply, etc? Or could you share your experience with us?

Sure, with great pleasure!
First and the main was an award of GHC Scholarship to attend and visit the Grace Hopper Celebration of Women in Computing (GHC) in 2016, Houston, Texas.
I read about this conference in one of the technical publics in social media. Grace Hopper Celebration (GHC) is the world’s largest gathering of women technologists. The scholarship application was open and at the same time, I decided to apply. The procedure was fairly standard: to apply, you had to be either a student in STEM in next year or faculty member, fill the online form with questions, write several essays with open questions, send your grades in university in English and ask your professor to write a reference letter.
Three months later, I received a letter that I was being awarded a scholarship and I am going to a conference.
Student and Faculty Scholarships include individual registration for the three-day conference, hotel accommodations for all days of the conference, meal card, a travel stipend to get to the conference form any point from the world. This conference gives amazing networking opportunities and to enter women tech communities. I met a big amount of encouraging women from all around the world and with some of them, I still keep in touch. Also each day there are a lot of tech talks and sessions, where you can meet female software engineers from different tech companies and ask the questions. And at the end of each day, there are several company dinners. And of course, there is a career fair where you can get a new job or internship for next summer.

After that, I was awarded by «Women Who Code» with a travel stipend and a discount ticket to attend the Google I/O tech conference by Google in 2017, Mountain View, California. I get information about this stipend from the mail list from Women Who Code. To apply for this stipend you also need to fill the online form and write an essay. This conference brings together developers from around the globe annually for talks, hands-on learning with Google experts, and the first look at Google’s latest developer products.

And at the third time, I was awarded with«Google Travel and Conference Grant» and get travel stipend and a ticket to attend ACM Celebration of Women in Computing womENcourage 2018 in Belgrade, Serbia. To be eligible for a grant to attend a conference in Europe, applicants must:

  • Be a woman working or studying computer science, computer engineering, or a technical field related to the conference subject (no residency restrictions apply)
  • Have a strong academic and/or professional background with demonstrated leadership ability.

WomENcourage brings together women in the computing profession and related technical fields to exchange knowledge and experience and provide special support for women who are pursuing their academic degrees and starting their careers in computing.
Through a programme packed with insightful topics and engaging educational and networking activities, womENcourage provides a unique experience of the collective energy, drive, and excellence that professional women share to support each other.

Also, I was attending WomenTechmakers Leads Summit in 2017 in Prague, Czech Republic and in 2018 Madrid, Spain. These summits also provided an excellent opportunity to communicate with leads women in technical fields from all around Europe.

You can reach me out via LinkedIn and ask more about each of these conferences and scholarships!

🎤 It is somehow a general notion that women find it hard to deal with STEM (Science, Technology, Engineering and Mathematics). Have you ever come across someone with the same thought process? If so, how did you deal with the situation?

Fortunately, I have never faced such situations, I have always been supported by my family, friends, teachers in school, professors, by women stem communities like WomenTechmakers and Women Who Code and people surround me.

🎤 What do you think, how we can help support the movement of women in STEM, Business and Activism?

We need to talk more about it! We need to talk more about unequal rights for women and men, that women are still paid less for the same kind of work. We need to help each other to fight with gender stereotypes about women in STEM, which still are. We need to organise more meet-ups and conferences about women in STEM and their achievements. Also, we need to talk about it since school times. That's why is needed to create different activities to encourage and inspire young girls to enrol into STEM faculties.

🎤 What advice would you give young women interested in a career in your field?

First of all, do not think that you are doing something wrong or someone else is better know. Believe in yourself and you will achieve everything you want. Even if there are some difficulties and something doesn't work out for you, it means that you are on the right track. It can always be difficult and incomprehensible at first. Try to find like-minded people, go to different thematic meetings, conferences, join different tech communities such as WomenTechmakers, Women Who Code, Google Developer Groups, Google Developer Student Club, Facebook Developer Circles, etc. Most of them are available in each country and in each region. Don't be afraid to come up first and have conversations. Networking is very important nowadays.
A lot depends on how you set yourself up.

🎤 What are your career aspirations?

As Natural Language Processing Engineer I definitely would like to improve existing voice assistants such as Google Assistant, Siri, Alexa, etc. I believe that we can make a much easier life for a lot of people around the world with them. Especially, for people with some disabilities.
I would like to continue to encourage and inspire women all around the world and give public talks about it. Also, I would like to be a mentor in future and help people to switch into the data science field and learn it from scratch. And would like to get several professional certifications in Data Science, Machine Learning and Cloud field.

🎤 How do you balance your study, work, hobbies, and personal life?

It's always been a tricky question for me. Since I'm a very responsible person and I really adore what I'm doing, I always trying to do my best and to improve everything. That's why I always spend a lot of time at work or studying. One of the things that help me is self-management. Fortunately, there are a lot of different books and courses about it nowadays.

🎤 What IT books, resources, and blogs do you read and recommend to others?

I have awesome-lists made by myself on GitHub (github.com/ElizaLo 🔗), so you can find much more there. Here are my top lists:

• Definitely, classic Machine Learning Course by Andrew Ng (link 🔗).
• Stanford CS229: Machine Learning | Autumn 2018 (link 🔗)
• Lecture Collection | Convolutional Neural Networks for Visual Recognition (Spring 2017) (link 🔗) by Stanford
• Introduction to Reinforcement Learning with David Silver (link 🔗) by Deep Mind, Google
• CS224N: Natural Language Processing with Deep Learning | Winter 2019 (link 🔗) от Стенфорд
• Get Started with Data Science Foundations (link 🔗) list of best courses by Coursera
• Machine Learning for Software Engineers (link 🔗)

Best Books:
• Deep Learning (Adaptive Computation and Machine Learning series) (link 🔗) by Ian Goodfellow.
• Pattern Recognition and Machine Learning, Bishop (link 🔗)
• Speech and Language Processing (3rd ed. draft) by Dan Jurafsky and James H. Martin (link 🔗)
• 100 Best Computer Vision Books of All Time (link 🔗)

Also, you can find recent research papers on arXiv or on Papers With Code on any topics you like.

🎤 What’s the best way to keep up to date with what you're doing?

Feel free to add me and contact:

LinkedIn: @yelyzaveta-losieva
GitHub: @ElizaLo

My Open Source Projects:

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