How remote work helped Kseniia Gubina
Notchup is a platform that has given a new life and an all-new definition to remote working. Talents are working from across the world, as a team, to bring about a revolution in work.
The concept of remote-first revolves around working from anywhere - where you can deliver maximum productivity. With the size of cubicles and cabins decreasing, the aim is to bring a sense of harmony and robust connectivity to your work desk. Many such talents work remotely from across the world and enjoy their work without contributing to traffic congestion or space sharing.
As proof of this, I speak to Kseniia, technical talent, or a 'tech-monk,' in Notchup's dictionary.
Kseniia is also someone who has scaled the odds to be where she is today. Since I want to know a bit about her background, I begin my conversation with a question about her journey to date. And, Kseniia shared with me how she and her family left the war to settle in Serbia. She reminisces how the war forced several to come out and explore opportunities outside. It was not easy for her with a small family to find a company that were willing to hire based on the unsecure situation – until she found Notchup. I am proud to say that my company does not discriminate based on gender, cultural background, religion or when people are seeking refuge from war.
To my questions about her specialization, Kseniiia answers that she is a data scientist who worked in a bank. As a data scientist, she is responsible for developing models to predict redemptions. Now that she is with Notchup, I ask her how she came to know about the platform and all the other exciting details of her joining.
To this, Kseniia replies: "I did not know about the platform. Actually, a talent acquisition specialist from Notchup contacted me and told me to apply for the job on the platform". And, I want to know if she is happy with the job, and how it is going! Kseniia now works as a data scientist, creating a machine learning algorithm and enjoying her work.
Kseniia is quick to answer in the affirmative. However, she enlarges on the challenges she is facing since, unlike in her earlier job, she is not just designing a product but is responsible for its implementation too! So, was she finding it difficult? Kseniia says it's tough, but she is taking up the challenge with all its complexities and enjoys it too.
My next question to her is how she finds the change in the working environment (she works from home). She smiles and replies, "I quite enjoy working from home. I do not have to travel anywhere; I can work from home and at my pace".
She further explains that with no traveling involved, multiple advantages come with Notchup. Kseniia feels the most crucial takeaway from Notchup is the ability to work from anywhere. She also thinks that with remote working comes perks such as flexible work hours and working in safe, well-known, and calm surroundings.
Since she is a data scientist, I question her about her team and if she connects with them often. Kseniia replies that she does most of her work alone. But she also connects with her team for quick review meetings and correlations on any project-related work. She also mentions how most of her team members work from India.
I wind up my call with one last query: how does she find Notchup at large?
Kseniia signs off by stating she finds Notchup a great community to work in and also urges fellow remote workers to use all sources and services wisely to make the most of the opportunity.
I end my call with my thoughts on how several such global tech talents have beaten the odds to be here today. With platforms like ours—Notchup—it's possible to bridge the gap between the worldwide talent pool and those organizations looking for just brilliant minds like Kseniia to take up their projects!
A great start towards a very positive and ideological future of work.
Kseniia is a data scientist. She is experienced in prediction of customer’s behaviour based on machine learning methods especially in finance industry. Previous achievements include complicated models to predict early redemptions of retail products in large bank.