David Prokhorov · CV
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§ 01 · Index

David Prokhorov

Entrepreneur · ex-ML engineer · dApp Product Owner at 1inch Labs

Available for select projects
§ 02

Summary

Entrepreneur & builder with 7+ years in ML, data engineering, and DeFi. Architected and shipped complex products end-to-end, leading cross-functional teams. Strong math foundation; hands-on with scalable ETL, web apps, and ML models.

§ 03

Experience

2025 — now

1inch Labs

dApp Product Owner
DEX aggregator
  • Transformed team productivity by implementing Agile practices: daily standups, sprint planning, retrospectives. Doubled development velocity and increased team autonomy through structured communication.
  • Led a 20+ people cross-functional dApp team (PMs, FE, Design, PA, QA) from roadmap to on-time releases; set priorities, clarified ownership, and removed blockers.
  • Scaled leadership capacity by coaching team members through regular feedback and growth plans. Promoted 2 new Lead positions to enhance team autonomy.
  • Strengthened product stability by implementing Sentry monitoring, Mixpanel alerts for user-flow outliers, and SRE practices for dApp APIs.
  • Optimized QA operations by defining standards for manual and automated testing, accelerating release cycles.
  • Delivered 1inch expansion to Solana network with intent-based and cross-chain swap integration.
  • Shipped comprehensive dApp rebranding: new Simple Swap interface, PRO trading mode with TradingView charts, 16+ landing pages.
2023 — 2025

1inch Labs

Crypto Portfolio Tracker Product Owner
DEX aggregator
  • Shipped portfolio tracker to production; reached 2k DAU / 10k WAU / 30k MAU, 5–10 rps average load, 99.9% availability, NPS 33.5%. Led cross-functional team of 7 (PM, SWE, DA, FE, Design, DevOps).
  • Designed PnL computation over arbitrary time windows for on-chain assets within user portfolios.
  • Conducted 100+ user interviews to refine product UI/UX and drive iterative improvements.
  • Introduced multi-wallet concept, aggregating all on-chain addresses into unified portfolios.
  • Launched Portfolio Highlights of the Year: tried by 10k users, +30% WAU during the campaign.
  • Led end-to-end development of explore.1inch.io, a DeFi investment comparison tool covering 2000+ opportunities across 30 protocols and 12 blockchains, achieving 3k MAU.
2022 — 2023

Quantor

Co-Founder
Blockchain analytics platform Acquired
  • Successfully exited — Quantor was acquired by 1inch Labs, becoming the foundation for their portfolio tracker product.
  • Architected and built a reliable ETL system for 3 EVM (eth, polygon, bsc) blockchains, managing over 100TB of data with a daily ingestion of 50GB.
  • Built high-performance crypto token price engine from DEX swaps using graph algorithms (Rustworkx) with recency/activity weighting; block-level prices for 10k+ tokens across 3 chains.
  • Engineered a profitability calculation system for Uniswap V3 positions, including fees, impermanent loss (IL), APR, and PnL.
  • Prototyped anti-fraud graph search across 250M addresses / 750M edges.
  • Optimized ClickHouse databases for fast API queries using AggregationMergeTrees.
2024 — now

AESC MSU alumni community

Co-Founder
Alumni community
  • Co-founded and built alumni community for AESC MSU boarding school, growing to 350+ members across multiple countries.
  • Developed brand identity including logo design and visual guidelines for community recognition.
  • Organized and executed 10+ international networking events across Serbia, UAE, Russia, Germany, USA, Kazakhstan, and UK, fostering global alumni connections.
2021 — 2022

Mellow Finance

Quantitative Researcher
Trustless automatic DeFi strategies
  • Built an open-source backtesting framework for on-chain strategies across Uniswap V3, Aave, Gearbox; increased strategy throughput.
  • Researched and implemented production-ready Uniswap V3 active liquidity management strategies.
2019 — 2021

Deeplight Technologies

ML Engineer
AI assistance for oil & gas industry
  • Built oil production prediction model outperforming industry baselines by 5%.
  • Improved forecast accuracy of oil production prediction by 2-3% via training methods robust to non-stationary data.
  • Developed a lithology classification model using borehole logging data that achieved 1st place in the international Xeek.ai FORCE competition.
  • Contributed to internal framework for reproducible ML pipelines.
  • Implemented well stimulation technique probability prediction models.
2018 — 2019

Samsung AI Center

Intern Engineer
Visual Understanding Lab
  • Engineered an internal benchmarking system to evaluate the robustness of SLAM algorithms against state-of-the-art solutions, simplifying progress tracking.
  • Co-authored and presented a research paper on the robustness of SLAM systems at the MVA 2019 conference in Tokyo.
§ 04

Education

Lomonosov Moscow State University

BS & MS, Faculty of Mechanics and Mathematics
August 2014 — August 2021

Thesis: Learning on Non-Stationary Data — methods to improve model robustness under distribution shift.

§ 05

Competitions

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Publications