Low Latency Quantitative Researcher, Asian Markets (FX, Equities, Commodities) in Niedergebra

Legacy Shift is focused on redefining the landscape of high-frequency trading across global markets. The firm combines a bold vision with a strong commitment to innovation, using cutting-edge technology to gain a competitive edge. By continuously pushing technical and quantitative boundaries, Legacy Shift seeks to unlock opportunities where others encounter limitations.Team members are encouraged to experiment, iterate, and contribute to a culture of forward-thinking problem solving that directly impacts trading performance and market presence.The RoleWe are looking for an experienced Quantitative Researcher to develop systematic, high-frequency trading strategies across Asian financial markets.You will research predictive signals from high-frequency market data, apply statistical and machine-learning techniques to identify persistent sources of alpha, and translate those signals into strategies that can operate successfully in a low-latency production environment.This is a highly hands-on role at the intersection of quantitative research, machine learning, market microstructure and algorithmic trading. You will work directly with traders and low-latency engineers, taking ownership of the research process from raw order-book data and hypothesis generation through backtesting, execution design and live deployment.A strong understanding of Asian market structure is essential. You should understand not only how to build predictive models, but how exchange mechanics, liquidity, queue dynamics, transaction costs and latency determine whether a statistical edge can actually be monetised.ResponsibilitiesResearch, develop and improve systematic and high-frequency trading strategies across Asian equities, FX and/or commodities.Develop predictive signals from tick-level, order-book and other high-frequency market data.Apply machine-learning and statistical techniques to problems including short-term price prediction, liquidity forecasting, execution and market-state classification.Analyse market microstructure across Asian venues, including order-book dynamics, queue behaviour, adverse selection, liquidity regimes and intraday patterns.Build rigorous research and validation frameworks to distinguish genuine predictive signals from overfitting, data leakage and statistical artefacts.Design realistic backtests incorporating transaction costs, latency, fills, queue position and other execution constraints.Evaluate signal decay and determine the latency and execution requirements necessary to capture an identified edge.Work closely with traders and execution researchers to translate predictive signals into executable algorithmic strategies.Analyse market microstructure across Asian venues: order-book dynamics, adverse selection, liquidity regimes and intraday seasonalityContinuously research new datasets, modelling approaches and market behaviours that can generate additional trading edge.Requirements3+ years of professional quantitative research or algorithmic trading experience within an HFT firm, proprietary trading firm, market maker or highly quantitative trading team.Excellent Python/C/C++ design and programming skillsStrong knowledge of Asian market microstructure across equities, FX and/or commoditiesPractical experience applying machine-learning techniques to financial market data, with a clear understanding of overfitting, feature selection, non-stationarity and out-of-sample validation.Understanding of the practical constraints of low-latency trading, including execution costs, latency, market impact, adverse selection and fill probability.What We OfferDirect access to full exchange order-book and tick data across all traded markets from day oneRapid research-to-production pipeline — ideas can go live in weeks, not quarters30 days holiday and gym membershipFull relocation package and visa sponsorship where required #J-18808-Ljbffr