Senior Trading Behavior & Flow Risk Analyst

Who We Are  Freedx is a newly established cryptocurrency exchange focused on building a scalable, compliant, and liquidity driven trading platform. Our team brings deep experience across crypto exchanges, payments, market structure, and financial infrastructure. Freedx is built for serious traders and emerging markets, with a clear focus on unit economics, operational discipline, and sustainable growth.  Our Vision  Freedx aims to be a trusted global exchange by combining strong liquidity, efficient onboarding, and disciplined growth execution. We focus on long term retention and monetization rather than vanity metrics, ensuring that growth directly translates into trading volume, revenue, and profitability. 

Role Overview We are looking for a highly analytical professional with deep understanding of trading behavior, market microstructure, and large-scale participant analysis.

The role focuses on identifying scalable and repeatable trading behavior, evaluating participant quality beyond surface-level profitability metrics, and building systems that distinguish persistent edge from noise across large populations of traders.

The ideal candidate may come from institutional trading, market making, brokerage risk, execution, proprietary trading, or quantitative research environments.

Responsibilities • Analyze large-scale trading behavior across tens of thousands of accounts and millions of trading events. • Build frameworks to evaluate long-term trader quality, consistency, and behavioral stability. • Develop participant scoring systems based on execution behavior, risk profile, consistency, and behavioral patterns rather than simple PnL metrics. • Identify persistent signals related to execution quality, position management, holding behavior, directional bias, exposure concentration, and performance drift. • Research repeatability of trading behavior across different market regimes and non-stationary environments. • Detect behavioral deterioration, adverse selection, flow toxicity, style drift, and execution inefficiencies. • Design frameworks for participant segmentation, risk profiling, and flow classification. • Evaluate participant quality using metrics such as MAE/MFE, drawdowns, position sizing, holding behavior, rolling performance drift, exposure concentration, and tail risk characteristics. • Work with large-scale datasets and real-time monitoring systems. • Collaborate with engineering teams on automated decision systems, risk infrastructure, and real-time analytics. • Develop robust analytical logic capable of adapting to changing market conditions and evolving participant behavior.