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Metro location, mid-level (0–4 yrs) band, broad full-stack plus quant skillset increases applicant competition.
Role requires trading-specific domain knowledge (TCA, market microstructure, asset classes), so background fit is highly domain-sensitive.
Explicit 0–4 years requirement plus mandatory SQL and React and platform tooling implies high filtering strictness.
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Develop and maintain transaction cost analysis (TCA) frameworks and real-time visual tools to assist trading decisions across fixed income and equity products.
Enhance broker performance evaluation through quantitative scorecards impacting routing and execution strategies.
Conduct market microstructure research and build scalable data pipelines for analytics to improve trading outcomes and execution efficiency.
0–4 years experience in quantitative analytics, data engineering, or financial modeling.
Proficiency in SQL and React; Python preferred.
Bachelor’s degree in a quantitative field (e.g., Engineering, Mathematics, Finance).
Familiarity with asset classes, portfolio theory, investment strategies, and tools like Azure Cloud, Snowflake, or Streamlit.
Technical expertise in building trading analytics platforms combined with practical market insight.
Experience collaborating closely with traders and investment teams to align analytics with business and trading goals.
Ability to handle large-scale execution data and translate complex data into actionable intelligence for improving trading performance.