About Arraxis

We ship data products and document what we did end to end. Consulting engagements often follow unreadably large generated pipelines, or a mandate to place data cleanly and keep models aligned with fresh traffic.

The Team

PS

Pavel Sulimov

Data Science, Research, and Teaching
ZHAW Institute of Computer Science, Winterthur

Lecturer and researcher in quantum and applied machine learning at ZHAW, and academic lead of the Innosuisse AI Booster Expert Group on Quantum Algorithms. Pavel has 9+ years in applied data science across bioinformatics, banking, network analysis, and online services. He is a PhD in Theoretical Computer Science from HSE University (Moscow). His publication record includes peer-reviewed work in computational biology journals and conference proceedings. Before moving into research and teaching, he led data science teams at BetVictor and Sberbank.

  • Lecturer and Quantum AI Researcher at ZHAW
  • Academic Lead, Innosuisse Quantum Algorithms group
  • Former Lead Data Scientist at BetVictor
  • PhD in Theoretical Computer Science
  • Publications in peer-reviewed computational biology venues
Quantum ML Reinforcement Learning Python PySpark Deep Learning Network Analysis
LinkedIn
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Sergey Eremeykin

Software Engineering
Plata Card, Limassol

Software engineer with 10+ years of experience building data-intensive applications in Java, Kotlin, and Python. Sergey currently designs backend systems at Plata Card (fintech). He previously built microservices at Arrival, the British EV startup, and spent four years at HeadHunter (hh.ru), Russia's largest job platform, where he led the ads service that became the company's second-largest revenue source. He holds a Master's in Mechatronics from Bauman Moscow State Technical University and has published research on control systems.

  • Software Engineer at Plata Card
  • Built microservices and federated GraphQL at Arrival
  • Led ads platform at HeadHunter, 4x revenue growth
  • Master's in Mechatronics, Bauman Moscow State Technical University
  • Published research on vibration control systems
Java Kotlin Spring Microservices GraphQL Docker
LinkedIn

Why Arraxis

Raw metrics and logs rarely speak for themselves. Structure, modeling, and honest write-ups turn them into something a team can act on.

We ship products and publish narratives in the same voice: what we tried, what broke, and what we measured. Each write-up follows the same five sections: Problem, Challenge, Solution, Implementation, Summary.

Pavel handles the data science, ML, and quantum computing side. Sergey handles the backend systems and infrastructure. Between the two of us, we cover the path from prototype to deployment.

Work with us

Free assessment or booked call. Both yield a written proposal.

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