EdgeFlowLab · Quantitative Research

Mean-reversion alpha
at institutional scale

Statistically validated edge. Ready to scale.

Get in Touch
Infrastructure

Compute we are scaling

Research throughput at EdgeFlowLab is bound by compute, not by ideas. We are actively sourcing accelerator capacity — purchase, lease or evaluation — and talk directly with vendors, OEMs and regional distributors.

AI Accelerators
Monte Carlo permutation testing, multi-regime parameter sweeps and ML-based alpha modelling are GPU-bound. Accelerator throughput sets how many hypotheses we can falsify per week — the binding constraint on research output.
NVIDIA MetaX Huawei Ascend No vendor lock-in
CPU Compute
Walk-forward validation runs thousands of independent windows per instrument, each with a fresh engine and no shared state. The workload is embarrassingly parallel — wall-clock time scales almost linearly with core count.
High core count Bare metal NUMA-aware
Storage & I/O
Tick-level history from 2019 onward across crypto perpetuals, FX and index futures, extended every day. Backtests are read-heavy and random-access, so sustained IOPS matter to us far more than sequential bandwidth.
NVMe Sustained IOPS Tiered archive
Network & Colocation
Live execution is latency-sensitive: a passive limit order is only worth placing when the round trip to the venue is predictable. We are evaluating colocation and low-latency transit near the exchanges we trade.
Colocation Low latency Redundant uplinks
Evaluating
NVIDIA MetaX Huawei Ascend AMD Instinct Intel Gaudi
Suppliers & distributors
If you represent a vendor or distribute its hardware, we are interested in current availability and lead times, pricing for outright purchase and for multi-year lease, evaluation or loaner units we can benchmark against our own workloads, and what support looks like in practice. Technical specifications are more useful to us than brochures — send them to alpha@EdgeFlowLab.com.

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
Join the Lab

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.
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.
Contact

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.

alpha@EdgeFlowLab.com
Investor inquiries & pitch deck

Request investor materials

Or reach us directly at alpha@EdgeFlowLab.com