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Tier-1 brand, mid-level metro quant analytics role increases competitive applicant density.
Role requires specialized equity market and quant analytics experience, limiting cross-industry transferability.
Explicit 4–6 years, equity markets experience, Python/KDB+ and data pipeline requirements increase filtering.
Work with global Morgan Stanley Quantitative Research teams providing execution consulting to reduce algorithmic trading slippage and enhance algo performance through bespoke Transaction Cost Analysis (TCA).
Conduct in-depth equity market structure research and analysis including market impact, dark liquidity, smart order routing, and algorithmic order placement.
Build and analyze data processing pipelines and enriched datasets from diverse internal and external sources to support equity trading models.
4-6 years of experience in the financial sector with direct practical experience in equity markets.
Bachelor's or Master's degree in Finance, Economics, Mathematics, or equivalent professional qualifications (CA, CFA, FRM, MMS, MBA); Engineering degree preferred.
Proficiency in mathematical/high-level programming languages such as Python or R, and practical mastery of data analysis at scale.
Strong written and verbal communication skills; exposure or knowledge of equity and equity derivatives products is desirable.
Experienced in building and optimizing algorithmic trading models with a strong quantitative research background across finance, econometrics, statistics, or machine learning.
Comfortable working in Asia time zone with global teams involving complex equity market data and systematic trading strategies.
Able to decompose complex financial problems into manageable components and present practical, data-driven solutions using advanced analytical and programming skills.