Data Analyst (Quantitative Risk)

About Us: Hytech is a leading management consulting firm headquartered in Australia and Singapore, specialising in digital transformation for fintech and financial services companies. We provide comprehensive consulting solutions, as well as middle- and back-office support, to empower our clients with streamlined operations and cutting-edge strategies. With a global team of over 2,000 professionals, Hytech has established a strong presence worldwide, with offices in Australia, Singapore, Malaysia, Taiwan, Philippines, Thailand, Morocco, Cyprus, Dubai and more.

Role Overview:

As a Data Analyst in the Dealing Team, you will act as a strategic partner in driving data-informed decisions on real-time trading actions. Your primary mission is to provide actionable insights and performance-driven analysis to support client trading management – including client profiling, behavioral modeling, trade evaluation, and real-time liquidation strategies. This is a hands-on role requiring strong analytical skills, business sense, and the ability to turn data into immediate, high-impact decisions.

Key Responsibilities:

Conduct quantitative risk assessments for high-profitability clients, and advise senior management on order-flow routing decisions.

Enhance and develop the Trading Book internalization system to optimize the company's risk–return profile.

Oversee market risk by managing hedging of book exposures to liquidity providers (LPs) in line with management directives.

Analyze client trading behavior across different segments to identify patterns, risk profiles, and strategic opportunities.

Support the Dealing team in real time by delivering data-backed recommendations on liquidation decisions, hedging actions, and trade exposure assessments.

Build dashboards and monitoring tools to track real-time client activity, market impact, and internal position exposure.

Collaborate with Product, Risk, and Engineering teams to ensure analytics align with business objectives and system capabilities.

Perform deep-dive investigations into high-PNL-impact events, abnormal trading behaviors, or strategy loopholes.

Analyze trade lifecycle metrics—such as entry/exit timing, slippage, and holding time—to support pricing and execution optimization.

Assist in refining internal trading policies based on behavioral trends and market impact.

Qualifications:

Minimum 3+ years of experience in trading analytics, brokerage, or data roles related to real-time trading activity.

Proficiency in SQL (including complex queries, joins, and performance optimization).

Experience in Python for data processing, statistical analysis, and automation scripting.

Solid knowledge of trading products (e.g. FX, CFDs, derivatives) and client behavior in leveraged markets.

Understanding of trading operations, including exposure management, pricing, slippage, and market depth, is highly advantageous.