Valentin Panovsky
Data Infrastructure and AI Solutions Consultant
Data management
Data governance
AI
An expert in data management and data/AI platform development with 10 years of experience. He has launched teams from scratch and restructured them to cover all key areas: Data Engineering, BI/Analytics, Data Science & AI, and Data Governance. He has deep expertise in DWH development, migration from legacy stacks, building end-to-end analytics infrastructure, and implementing ML solutions, as well as practical experience implementing open-source solutions. He has spoken at conferences such as SmartData, Highload, TechWeek, and others. He is an associate professor and researcher at MAI NRU. He holds a PhD in Physics and Mathematics.
Data management
Data governance
AI
Education
- Moscow Aviation Institute (National Research University) (Candidate of Physical and Mathematical Sciences, “Mathematical Modeling, Numerical Methods and Software Suites” and “System Analysis, Management and Information Processing”, 2017)
- Moscow Aviation Institute (National Research University) (specialist's degree, applied mathematics, 2014)
- Moscow Aviation Institute (National Research University) (specialist's degree in economics and enterprise management, 2014)
Expertise
I spent the first half of my career working in various fields to gain relevant hands-on experience and gain a wealth of experience. I worked as an engineer, analyst, and developer of ML models and algorithms in various business sectors, including ecommerce/retail, FMCG, ecology, science & R&D, EdTech, InsurTech, MedTech, and FunTech. Subsequently, as a manager and player-coach, I focused on creating and/or reorganizing analytics or data management departments from scratch (including the development and implementation of a data platform and DWH).
During the data platform implementation, I technically interacted with both VPS/VDS-based infrastructure implementations (Hetzner Data Center, GPU-Mart) and those based on traditional cloud providers (Selectel, Yandex Cloud, Timeweb). I also assembled the analytics framework from both proprietary and open-source solutions (depending on available budgets and business priorities).
When organizing the department, I adhered to the principles of maximizing team efficiency and lean talent development. My responsibilities encompass the full data cycle: from the development and operation of DWH and data platforms to analytics and the production launch of AI-based solutions.
Professional recognition
AI consulting
People Strategy
Growth & Investment