Crypto Quantitative Analyst (Global- Remote - Non.US)

📋 Description • Join Token Metrics Ventures LLC, the AI-powered crypto intelligence platform trusted by investors in 50+ countries, as we expand our global Data Science team with a Crypto Quantitative Analyst who will sit at the intersection of cutting-edge machine learning, high-frequency market data, and DeFi alpha discovery. • You will own the full lifecycle of quantitative research—from raw on-chain and order-book data ingestion to production-ready trading signals—working 100 % remotely with a distributed team of PhDs, former hedge-fund quants, and DeFi natives who ship code daily. • Design, back-test, and optimize systematic crypto strategies (stat-arb, momentum, mean-reversion, yield-farming, options flow) across spot, perpetuals, and DeFi pools; target Sharpe > 2 and max drawdown < 8 % on rolling 90-day windows. • Build Python pipelines that ingest terabytes of tick-level trade data, Ethereum traces, mempool events, and CLOB snapshots; store in columnar formats (Parquet, DuckDB) and apply GPU-accelerated analytics (RAPIDS, Numba) to find micro-alpha. • Research novel on-chain metrics—exchange flows, whale clustering, gas-usage patterns, staking derivatives—to create orthogonal factors that diversify traditional price-based signals and add 300–500 bps of uncorrelated return annually. • Implement rigorous risk engines: position-sizing via Kelly fractions, dynamic stop-loss derived from realized volatility regimes, tail-risk hedging with options skew, and real-time liquidation monitoring across 30+ centralized and decentralized venues. • Collaborate with engineering to deploy strategies live through FIX/REST/WebSocket connectors to Binance, OKX, Bybit, dYdX, and 1inch; ensure sub-second order placement and robust failover using Redis streams, Kubernetes, and serverless AWS Lambdas. • Present weekly “alpha demos” to the investment committee—clear storytelling with Jupyter notebooks, interactive Plotly dashboards, and concise slide decks that translate statistical significance into actionable allocation decisions for a $100 M+ AUM book. • Contribute to Token Metrics’ retail and institutional products: convert your best signals into scalable rating factors that feed our AI rankings, price-prediction models, and newsletter insights, directly impacting 50 k+ paying subscribers worldwide. • Stay ahead of the curve—experiment with Rust-based HFT micro-services, zero-knowledge proof datasets, MEV extraction back-tests, and cross-chain liquidity fragmentation arbitrage—then publish findings in our quarterly “Quant Pulse” research report. • Mentor junior analysts on statistical best practices (multiple-hypothesis testing, walk-forward validation, Bayesian updating) and foster an open-source mindset by releasing sanitized back-testing frameworks that grow the broader crypto-quant community.