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Sergey Velts

Founder & CTO – Cybertonica

Professional Background

Sergey Velts is a highly regarded expert in data science, particularly within the realms of FinTech and computer security. With his deep expertise, he has successfully founded and served as the Chief Technology Officer (CTO) of two innovative startups, further establishing his reputation as a leader in the technology sector. Sergey has consistently demonstrated a strong commitment to pushing the boundaries of technology and improving the intersection of financial services and data analysis.

His career includes significant tenure at various prestigious organizations, where he has held critical roles that leveraged his expertise in big data and data-driven solutions. Notably, he served as Big Data Team Lead at Sberbank Labs, a position where he spearheaded the development of data-centric innovations aimed at transforming traditional banking practices. His leadership in this role has made considerable contributions to enhancing the financial industry’s capabilities through advanced data solutions.

In addition to his experience in the corporate sector, Sergey has also played a vital role in academia. He was an assistant at Moscow State Technical University (MГТУ), where he shared his knowledge with aspiring data scientists and software engineers. His dedication to education highlights his belief in nurturing the next generation of technology leaders. Sergey’s expansive career path highlights a perfect blend of practical experience and academic involvement, demonstrating his multifaceted skill set.

Education and Achievements

Sergey Velts has a solid educational foundation that underpins his extensive expertise in data science and machine learning. He undertook advanced studies as an аспирант focusing on computer security and machine learning at Moscow State Technical University (МГТУ), where he achieved an impressive score of 4.9. His rigorous academic training in these critically important fields provided him with the necessary skills to thrive in technology-driven environments.

In addition to his studies at МГТУ, Sergey further honed his analytical capabilities at the Yandex School of Data Analysis. This prestigious institution is known for cultivating talent in data science and analytics, and his time there equipped him with advanced methodologies and the latest tools in data science. Sergey’s combination of technical acuity and innovative thinking has positioned him as a vital force in the FinTech landscape.

Notable Achievements

Throughout his career, Sergey has been instrumental in driving the success of various key projects across multiple organizations. At Cybertonica Ltd, he not only founded the company but also strategically directed its technological advancements. His leadership style and strategic foresight have been paramount to the startup's growth and innovation trajectory, making Cybertonica a notable name within the FinTech sector.

As part of his impressive credentials, Sergey's contributions at Sberbank Labs involved leading a talented team dedicated to exploring and implementing big data solutions. The focus was on optimizing banking operations and enhancing client service through sophisticated data analysis techniques, showcasing his ability to effectively bridge technology and financial services.

Before his leadership roles, Sergey also gathered extensive experience as a developer. His career commenced with multiple technology positions, including a Java Developer role with Jet Infosystems and work as a System Analyst at БФТ. These foundational experiences allowed him to refine his technical competencies, leading to subsequent team lead roles in companies such as Diahelp, where Sergey advanced to senior software developer before taking on more managerial responsibilities.

Overall, Sergey Velts's career is characterized by his continuous drive for innovation, expertise in data science for FinTech, and proactive approach to developing solutions in computer security. His commitment to advancing technology not only serves the organizations he works with but also contributes positively to the broader tech ecosystem.

Highlights

Jun 20 · linkedin

Nice article about BNPL in Middle East.

"The youngest demographic members prioritise personalised shopping experiences over concerns about data-sharing, in contrast to millennials who expressed greater reservations about sharing their data."

This is interesting. Personally, I'm definitely on privacy protection side. That's why I try hard to ensure that proper cryptography is present in all APIs, including (relatively) novel things such as oblivious transfer and PMT. Behaviour analysis is from the same category – then you have lots of PII you can probably do without behaviour analysis but try to do good scoring when you only know session info and phone number.

Just curious how much privacy GenZ is ready to give up for convenience.  For example, I know a bank, they are super convenient and innovative. One of their innovations is doing face recognition in mobile device’s phone gallery for scoring purposes. Maybe GenZ doesn’t not know (yet) what they are ready to give up...

https://lnkd.in/dhAhd28w

Apr 28 · linkedin

Session monitoring for better BNPL scoring

Credit scoring and fraud monitoring are related because different fraud attacks can result in defaults. That’s why we started to help BNPL companies using our session and behavior monitoring tech.

The idea is that we collect device fingerprints, behavior information, then do link analysis, feature engineering and then return Feature Vectors (dim > 100) to client’s scoring system in real-time using Score Session API. We also return indicators of compromise like bot, new device and so on.  The features give uplift because they help to reduce real-time fraud (etc. multiple applications by the same person from emulators, fraud rings and so on).

Finally, let’s look how neural networks use these features and try to separate good and bad BNPL loan application sessions. Below is a visualization of autoencoder after different number of epochs of training. Blue/orange - train, green/red - test good/default correspondingly.

#scoring #ml #bnpl #cybertonica #visualization

Related Questions

How did Sergey Velts develop his expertise in data science for FinTech?
What innovations has Sergey Velts introduced during his time as CTO at Cybertonica?
What inspired Sergey Velts to focus on computer security and machine learning?
How has Sergey Velts's education at МГТУ and Yandex School influenced his career?
What challenges has Sergey Velts faced while leading teams in big data at Sberbank Labs?
Sergey Velts
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Location

Liverpool Street, England, United Kingdom