Head of Quantitative Strategies

Welcome to MultiBank Group, a global financial pioneer established in 2005 in California and now proudly headquartered in Dubai, UAE. We specialize in delivering cutting-edge trading technology, unparalleled liquidity, and exceptional customer service. Our extensive range of financial products includes Forex, Metals, Shares, Indices, Commodities, and Cryptocurrency CFDs. Join our thriving community of over 2 million clients across 100 countries, contributing to a daily trading volume exceeding US$ 35 billion.

As a heavily regulated institution with oversight from 18+ financial regulators across 5 continents, and recipient of over 80 financial awards, MultiBank Group is devoted to innovation, excellence, and empowering our clients to achieve their financial goals.

As we continue to expand globally, MultiBank Group is seeking a Head of Quantitative Strategies & Execution to join MultiBank Exchange, our leading institutional Electronic Communication Network (ECN) providing deep liquidity, competitive pricing, and advanced execution solutions to financial institutions, brokers, hedge funds, proprietary trading firms, asset managers, and other professional market participants.

Our technology-driven platform delivers transparent access to global FX liquidity while enabling clients to optimize execution quality and trading performance.

Role Overview

MEX Exchange is seeking a Senior Quantitative Leader to build and lead its quantitative capabilities across liquidity, pricing configuration, execution and short-horizon trading research. The mandate is commercially focused: use high-frequency market and trading data to improve execution outcomes, reduce adverse-selection costs and support sustainable revenue growth. This is a hands-on leadership role at the intersection of quantitative research, low-latency trading technology and institutional electronic FX. The successful candidate will translate market-microstructure insights into measurable, production-ready improvements, working closely with liquidity management, technology, risk and commercial teams.

Key Responsibilities

Build and lead the quantitative function, define the research and implementation roadmap, recruit and mentor a growing quantitative team, and partner with liquidity, technology and commercial teams as the platform grows.

Analyse tick-level quotes, order-book data, client flow and execution events to understand markouts, adverse selection, latency, slippage, fill quality, rejects and liquidity-provider performance. Develop, test and deploy short-horizon predictive models for post-trade markouts, price movement, flow characteristics and execution quality; apply statistical and machine-learning methods where they offer demonstrable value. Design data-driven approaches to pricing optimisation, liquidity pool selection, and execution/routing configuration.

Quantify trade-offs between competitiveness, fill rates, client execution quality, liquidity-provider economics and platform revenue; recommend changes with clear performance metrics and safeguards. Partner with engineering to design reliable tick-data pipelines, event reconstruction, real-time analytics and low-latency model or decision services, including the controls needed for production use.

Establish rigorous research and deployment standards: out-of-sample validation, realistic simulation, transaction-cost analysis, controlled rollouts, model monitoring and rollback procedures. Evaluate the feasibility of other proprietary quantitative initiatives; where approved, lead research and implementation within agreed risk, capital and governance parameters.

Required Skills and Experience

8+ years of relevant professional experience in quantitative trading, electronic market making, systematic FX, execution research or market-microstructure-focused quantitative roles, including experience leading projects or teams. Deep understanding of institutional electronic FX markets, liquidity aggregation, execution protocols and the behavior of bank and non-bank liquidity providers.

Strong practical knowledge of high-frequency market data, order books, price formation, short-horizon signals, adverse selection, markouts and transaction-cost/execution analysis. Demonstrated ability to take quantitative research or models into production and measure their live impact on trading or execution performance. Advanced quantitative programming capability, particularly Python; strong familiarity with C++ and low-latency systems, SQL and high-volume time-series data environments.

Experience with FIX-based trading infrastructure is important. Sound grounding in statistics, time-series modelling, predictive modelling and robust backtesting; judgement in choosing interpretable statistical approaches versus more complex machine-learning methods. Practical experience using LLM-based tools responsibly for research ideation, code development,