Women in Tech: “All you need to do is to take the information and convert it into your expertise”

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A research study by The National Center for Women & Information Technology showed that “gender diversity has specific benefits in technology settings,” which could explain why tech companies have started to invest in initiatives that aim to boost the number of female applicants, recruit them in a more effective way, retain them for longer, and give them the opportunity to advance. But is it enough?

Four years ago, we launched a diversity series aimed at bringing the most inspirational and powerful women in the tech scene to your attention. Today, we’d like you to meet Liudmyla Taranenko, AI engineer at MobiDev.

Today’s Woman in Tech: Liudmyla Taranenko, AI engineer at MobiDev

Liudmyla Taranenko, an AI engineer at MobiDev (USA/Ukraine). Having a master’s degree in Applied Mathematics and Applied Economics, she started her career path from a data analyst position.

Having acquired expertise in Machine Learning, mathematical modeling, optimization methods, and business analysis, she is now inspired working with predictive analytics, recommendation systems, fraud detection, text analysis, CRM and finance data analysis.

What did your career path look like?

I was excellent in math class at school, and probably even then there was no doubt that I would continue to follow this path, as math has always been my best discipline. At the university, I studied applied mathematics in the Math & Computer Science Department. At that moment, I didn’t really care where in my future I could apply the specialty called “applied mathematics”. I was thinking of working in a bank or elsewhere. At the same time, I was more than sure that being skilled with mathematics would mean I would never have any problems with employment.

I first heard about Data Analysis and Data Science during my bachelor year, but I couldn’t have known then how quickly it would become such a mainstream science. When I started searching for my first job in tech, there were very few open positions in Data Science in my city. Then, even the employers seemed to have no understanding of what they expected from a candidate – the requirements were very different for the same job title. After each attempt to find a job, I carefully studied the questions which I had failed during the interviews I had completed, and finally I got my first job as a Data Analyst at an American company. Having acquired some expertise working with data, I was brave enough to conquer the Data Science world.

Now I am an AI engineer at MobiDev, but when I joined the company in 2019, there was still so much to learn about programming and communication with clients. I studied and learned a lot, gradually mastering new algorithms and completing more professional courses. Thanks to my team and our experienced leader, I was absorbed in the Data Science world, which at first had seemed so complicated to me.

I studied and learned a lot, gradually mastering new algorithms and completing more professional courses. Thanks to my team and our experienced leader, I was absorbed in the Data Science world, which at first had seemed so complicated to me.

The deeper you dive into your profession, the more expertise you get and the more you can share with the world. With time, I started telling about my tech experience in MobiDev’s blog and in publications related to demand forecasting using ML.

I love being a speaker on webinars related to Machine Learning and on the ML conference, and still feel a little shy and at the same time flattered when people message me on Linkedin to tell they are inspired by my work or to ask for advice.

Did you receive support from your family and friends?

Of course, I did! Since my very first steps along this path, I have received the best support ever from my Mom. She never stopped believing in me throughout my path in tech.

I met my true friends while I studied math at the university. Now they are all related to technologies, and we enjoy meeting together to discuss IT and AI innovations.

A day in Liudmyla’s life

My day starts with checking the inbox and corporate chats. Next, I help my mentees with their working agenda and make sure to get them set up on the tasks that require my input. I spend most of my time on our ongoing projects, acting both as AI Engineer and a tech lead.

It may sound trivial, but just knowing your goal and working hard for it can help to chop your way to a successful tech career.

Apart from doing research for my projects, I conduct internal tech research related to AI and Machine Learning, for example, how to improve data quality using unsupervised machine learning. Data analysis, and building and testing models are also a part of my work routine.

The afternoon is usually a time to share a progress update or do a demo for one of our clients. If not, then it’s time for me to make a presentation of our ideas or to do pre-sales calls.

What advice (and tips) would you give to women who want a tech career?

I never asked myself this question before, because for me, a tech career is something natural. The only recipe that can be applied to the tech industry is never stop learning. It may sound trivial, but just knowing your goal and working hard for it can help to chop your way to a successful tech career.

The only place where the stereotypes are still alive is the human mind.

In reality, all you need to do is to take the information and convert it into your expertise.

More Women in Tech:

For even more Women in Tech, click here

The post Women in Tech: “All you need to do is to take the information and convert it into your expertise” appeared first on JAXenter.

Source : JAXenter

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