EdgeFlowLab · Quantitative Research

Mean-reversion alpha
at institutional scale

Statistically validated edge on crypto perpetual futures. Walk-forward tested. Out-of-sample confirmed. Ready to scale.

Technology stack

Signal Research
Systematic discovery and validation of alpha signals using walk-forward methodology, Monte Carlo permutation testing and multi-regime robustness analysis. Every signal survives out-of-sample before deployment.
Python Walk-Forward Monte Carlo OOS Validation
Execution Layer
Low-latency order routing engine designed for crypto perpetuals. Passive limit order logic, fill probability modeling, slippage-aware position sizing and real-time breakeven monitoring per instrument.
WebSocket Order Routing Slippage Model Co-location
Data Infrastructure
Tick-level historical data from 2019 onward across BTC, SOL and major instruments. Structured data pipeline from raw OHLCV to labeled signal features, with continuous quality validation and gap detection.
Tick Data OHLCV Feature Store
Risk & Monitoring
Real-time drawdown limits, rolling OOS Sharpe tracking, position-level exposure controls and automated kill-switch logic. All risk parameters are pre-configured — no manual intervention required in normal operation.
Drawdown Limits Kelly Sizing Kill-Switch Rolling OOS

Open positions

We are building an institutional-grade quantitative trading system from first principles. If you think in signals, systems and probability — we want to work with you.

Research · Full-Time
Quantitative Researcher
Design and validate systematic alpha signals on crypto perpetual futures and global macro instruments. You will own the full research lifecycle — from hypothesis to out-of-sample evidence.
  • Strong background in statistics, mathematics or physics (PhD preferred)
  • Hands-on experience with walk-forward validation, Monte Carlo methods
  • Python proficiency: pandas, numpy, scipy, statsmodels
  • Familiarity with market microstructure and execution costs
  • Track record of generating statistically robust trading signals
Remote · Latam / Europe Research
Engineering · Full-Time
Execution Systems Engineer
Build and optimize the low-latency execution layer for live crypto futures trading. You will work on order routing, fill probability models and real-time risk controls.
  • Experience building production trading systems (C++, Python, Rust)
  • Deep knowledge of WebSocket APIs, FIX protocol or exchange SDKs
  • Understanding of order book dynamics, slippage modeling, market impact
  • Experience with co-location, latency profiling or HFT infrastructure
  • Ability to reason about system reliability under adverse conditions
Remote · Timezone flexible Engineering
Data Science · Contract / Full-Time
Alpha Developer & Data Scientist
Expand our signal universe by researching alternative data sources, building feature pipelines and testing systematic hypotheses across multiple instruments and time horizons.
  • Experience with alternative data: on-chain, sentiment, order flow, macro
  • Proficiency in feature engineering and ML-based alpha modeling
  • Strong intuition for data quality, survivorship bias and overfitting
  • Familiarity with crypto market structure and DeFi data sources
  • Ability to translate academic research into testable hypotheses
Remote · Global Data Science

Apply now

All applications are reviewed by the founding team. We respond within 5 business days.
Submit Application →
No CV required at this stage — a well-written note about your work is more valuable. EdgeFlowLab is an equal opportunity employer. We evaluate candidates solely on merit and technical ability.

Ready to connect

The hardest part is done — the alpha is found and validated. We're looking for a partner to scale it into an executable system of institutional quality.

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Or reach us directly at [email protected]