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Tier-1 brand and metro location but niche quant skillset limits applicant density.
Quant trading and market-impact modeling are finance-specific skills with limited cross-industry transferability.
Requires specialized quant modeling, Python/QDB skills and industry experience, so filters are stringent.
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Research, design, and improve cash equity execution algorithms and central risk models for Citi's institutional clients and trading desks.
Analyze large market, order, and execution data to enhance quantitative models including optimal scheduling, market impact, and predictive signals.
Collaborate with traders, sales, technology, and risk teams globally to support model validation, performance tuning, and innovation in electronic trading.
Bachelor’s or Master’s degree in Finance, Mathematics, Engineering, Computer Science or related field.
Experience in quantitative modeling or analytics role, preferably in financial sector, involving statistical modeling and machine learning on large data sets.
Proficiency in statistical programming languages such as Python; experience with Q/KDB or time series databases is an advantage.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in developing and tuning quantitative models for algorithmic trading with knowledge of market impact and predictive signals.
Capable of handling complex data analysis and collaborating in a global multi-disciplinary team environment.
Comfortable working in a fast-paced setting involving multiple tasks and integration with trading and risk management functions.